datadog_api_client.v1.model¶

access_role¶

class AccessRole(*args, **kwargs)¶

Bases: ModelSimple

The access role of the user. Options are st (standard user), adm (admin user), or ro (read-only user).

Parameters:

value (str) – Must be one of [“st”, “adm”, “ro”, “ERROR”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

add_signal_to_incident_request¶

class AddSignalToIncidentRequest(*args, **kwargs)¶

Bases: ModelNormal

Attributes describing which incident to add the signal to.

Parameters:

add_to_signal_timeline (bool, optional) – Whether to post the signal on the incident timeline.
incident_id (int) – Public ID attribute of the incident to which the signal will be added.
version (int, optional) – Version of the updated signal. If server side version is higher, update will be rejected.

agent_check¶

class AgentCheck(*args, **kwargs)¶

Bases: ModelSimple

Array of strings.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

alert_graph_widget_definition¶

class AlertGraphWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

Alert graphs are timeseries graphs showing the current status of any monitor defined on your system.

Parameters:

alert_id (str) – ID of the alert to use in the widget.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – The title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (AlertGraphWidgetDefinitionType) – Type of the alert graph widget.
viz_type (WidgetVizType) – Whether to display the Alert Graph as a timeseries or a top list.

alert_graph_widget_definition_type¶

class AlertGraphWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the alert graph widget.

Parameters:

value (str) – If omitted defaults to “alert_graph”. Must be one of [“alert_graph”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

alert_value_widget_definition¶

class AlertValueWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

Alert values are query values showing the current value of the metric in any monitor defined on your system.

Parameters:

alert_id (str) – ID of the alert to use in the widget.
precision (int, optional) – Number of decimal to show. If not defined, will use the raw value.
text_align (WidgetTextAlign, optional) – How to align the text on the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of value in the widget.
type (AlertValueWidgetDefinitionType) – Type of the alert value widget.
unit (str, optional) – Unit to display with the value.

alert_value_widget_definition_type¶

class AlertValueWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the alert value widget.

Parameters:

value (str) – If omitted defaults to “alert_value”. Must be one of [“alert_value”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

api_error_response¶

class APIErrorResponse(*args, **kwargs)¶

Bases: ModelNormal

Error response object.

Parameters:: errors ([str]) – Array of errors returned by the API.

api_key¶

class ApiKey(*args, **kwargs)¶

Bases: ModelNormal

Datadog API key.

Parameters:

created (str, optional) – Date of creation of the API key.
created_by (str, optional) – Datadog user handle that created the API key.
key (str, optional) – API key.
name (str, optional) – Name of your API key.

api_key_list_response¶

class ApiKeyListResponse(*args, **kwargs)¶

Bases: ModelNormal

List of API and application keys available for a given organization.

Parameters:: api_keys ([ApiKey], optional) – Array of API keys.

api_key_response¶

class ApiKeyResponse(*args, **kwargs)¶

Bases: ModelNormal

An API key with its associated metadata.

Parameters:: api_key (ApiKey, optional) – Datadog API key.

apm_stats_query_column_type¶

class ApmStatsQueryColumnType(*args, **kwargs)¶

Bases: ModelNormal

Column properties.

Parameters:

alias (str, optional) – A user-assigned alias for the column.
cell_display_mode (TableWidgetCellDisplayMode, optional) – Define a display mode for the table cell.
name (str) – Column name.
order (WidgetSort, optional) – Widget sorting methods.

apm_stats_query_definition¶

class ApmStatsQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

The APM stats query for table and distributions widgets.

Parameters:

columns ([ApmStatsQueryColumnType], optional) – Column properties used by the front end for display.
env (str) – Environment name.
name (str) – Operation name associated with service.
primary_tag (str) – The organization’s host group name and value.
resource (str, optional) – Resource name.
row_type (ApmStatsQueryRowType) – The level of detail for the request.
service (str) – Service name.

apm_stats_query_row_type¶

class ApmStatsQueryRowType(*args, **kwargs)¶

Bases: ModelSimple

The level of detail for the request.

Parameters:

value (str) – Must be one of [“service”, “resource”, “span”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

application_key¶

class ApplicationKey(*args, **kwargs)¶

Bases: ModelNormal

An application key with its associated metadata.

Parameters:

hash (str, optional) – Hash of an application key.
name (str, optional) – Name of an application key.
owner (str, optional) – Owner of an application key.

application_key_list_response¶

class ApplicationKeyListResponse(*args, **kwargs)¶

Bases: ModelNormal

An application key response.

Parameters:: application_keys ([ApplicationKey], optional) – Array of application keys.

application_key_response¶

class ApplicationKeyResponse(*args, **kwargs)¶

Bases: ModelNormal

An application key response.

Parameters:: application_key (ApplicationKey, optional) – An application key with its associated metadata.

authentication_validation_response¶

class AuthenticationValidationResponse(*args, **kwargs)¶

Bases: ModelNormal

Represent validation endpoint responses.

Parameters:: valid (bool, optional) – Return true if the authentication response is valid.

aws_account¶

class AWSAccount(*args, **kwargs)¶

Bases: ModelNormal

Returns the AWS account associated with this integration.

Parameters:

access_key_id (str, optional) – Your AWS access key ID. Only required if your AWS account is a GovCloud or China account.
account_id (str, optional) – Your AWS Account ID without dashes.
account_specific_namespace_rules ({str: (bool,)}, optional) – An object, (in the form {"namespace1":true/false, "namespace2":true/false} ), that enables or disables metric collection for specific AWS namespaces for this AWS account only.
cspm_resource_collection_enabled (bool, optional) – Whether Datadog collects cloud security posture management resources from your AWS account. This includes additional resources not covered under the general resource_collection.
excluded_regions ([str], optional) – An array of AWS regions to exclude from metrics collection.
filter_tags ([str], optional) – The array of EC2 tags (in the form key:value ) defines a filter that Datadog uses when collecting metrics from EC2. Wildcards, such as ? (for single characters) and * (for multiple characters) can also be used. Only hosts that match one of the defined tags will be imported into Datadog. The rest will be ignored. Host matching a given tag can also be excluded by adding ! before the tag. For example, env:production,instance-type:c1.*,!region:us-east-1
host_tags ([str], optional) – Array of tags (in the form key:value ) to add to all hosts and metrics reporting through this integration.
metrics_collection_enabled (bool, optional) – Whether Datadog collects metrics for this AWS account.
resource_collection_enabled (bool, optional) – Whether Datadog collects a standard set of resources from your AWS account.
role_name (str, optional) – Your Datadog role delegation name.
secret_access_key (str, optional) – Your AWS secret access key. Only required if your AWS account is a GovCloud or China account.

aws_account_and_lambda_request¶

class AWSAccountAndLambdaRequest(*args, **kwargs)¶

Bases: ModelNormal

AWS account ID and Lambda ARN.

Parameters:

account_id (str) – Your AWS Account ID without dashes.
lambda_arn (str) – ARN of the Datadog Lambda created during the Datadog-Amazon Web services Log collection setup.

aws_account_create_response¶

class AWSAccountCreateResponse(*args, **kwargs)¶

Bases: ModelNormal

The Response returned by the AWS Create Account call.

Parameters:: external_id (str, optional) – AWS external_id.

aws_account_delete_request¶

class AWSAccountDeleteRequest(*args, **kwargs)¶

Bases: ModelNormal

List of AWS accounts to delete.

Parameters:

access_key_id (str, optional) – Your AWS access key ID. Only required if your AWS account is a GovCloud or China account.
account_id (str, optional) – Your AWS Account ID without dashes.
role_name (str, optional) – Your Datadog role delegation name.

aws_account_list_response¶

class AWSAccountListResponse(*args, **kwargs)¶

Bases: ModelNormal

List of enabled AWS accounts.

Parameters:: accounts ([AWSAccount], optional) – List of enabled AWS accounts.

aws_event_bridge_account_configuration¶

class AWSEventBridgeAccountConfiguration(*args, **kwargs)¶

Bases: ModelNormal

The EventBridge configuration for one AWS account.

Parameters:

account_id (str, optional) – Your AWS Account ID without dashes.
event_hubs ([AWSEventBridgeSource], optional) – Array of AWS event sources associated with this account.
tags ([str], optional) – Array of tags (in the form key:value ) which are added to all hosts and metrics reporting through the main AWS integration.

aws_event_bridge_create_request¶

class AWSEventBridgeCreateRequest(*args, **kwargs)¶

Bases: ModelNormal

An object used to create an EventBridge source.

Parameters:

account_id (str, optional) – Your AWS Account ID without dashes.
create_event_bus (bool, optional) – True if Datadog should create the event bus in addition to the event source. Requires the events:CreateEventBus permission.
event_generator_name (str, optional) – The given part of the event source name, which is then combined with an assigned suffix to form the full name.
region (str, optional) – The event source’s AWS region.

aws_event_bridge_create_response¶

class AWSEventBridgeCreateResponse(*args, **kwargs)¶

Bases: ModelNormal

A created EventBridge source.

Parameters:

event_source_name (str, optional) – The event source name.
has_bus (bool, optional) – True if the event bus was created in addition to the source.
region (str, optional) –
The event source’s AWS region.
status (AWSEventBridgeCreateStatus, optional) – The event source status “created”.

aws_event_bridge_create_status¶

class AWSEventBridgeCreateStatus(*args, **kwargs)¶

Bases: ModelSimple

The event source status “created”.

Parameters:

value (str) – If omitted defaults to “created”. Must be one of [“created”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

aws_event_bridge_delete_request¶

class AWSEventBridgeDeleteRequest(*args, **kwargs)¶

Bases: ModelNormal

An object used to delete an EventBridge source.

Parameters:

account_id (str, optional) – Your AWS Account ID without dashes.
event_generator_name (str, optional) – The event source name.
region (str, optional) –
The event source’s AWS region.

aws_event_bridge_delete_response¶

class AWSEventBridgeDeleteResponse(*args, **kwargs)¶

Bases: ModelNormal

An indicator of the successful deletion of an EventBridge source.

Parameters:: status (AWSEventBridgeDeleteStatus, optional) – The event source status “empty”.

aws_event_bridge_delete_status¶

class AWSEventBridgeDeleteStatus(*args, **kwargs)¶

Bases: ModelSimple

The event source status “empty”.

Parameters:

value (str) – If omitted defaults to “empty”. Must be one of [“empty”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

aws_event_bridge_list_response¶

class AWSEventBridgeListResponse(*args, **kwargs)¶

Bases: ModelNormal

An object describing the EventBridge configuration for multiple accounts.

Parameters:

accounts ([AWSEventBridgeAccountConfiguration], optional) – List of accounts with their event sources.
is_installed (bool, optional) – True if the EventBridge sub-integration is enabled for your organization.

aws_event_bridge_source¶

class AWSEventBridgeSource(*args, **kwargs)¶

Bases: ModelNormal

An EventBridge source.

Parameters:

name (str, optional) – The event source name.
region (str, optional) –
The event source’s AWS region.

aws_logs_async_error¶

class AWSLogsAsyncError(*args, **kwargs)¶

Bases: ModelNormal

Description of errors.

Parameters:

code (str, optional) – Code properties
message (str, optional) – Message content.

aws_logs_async_response¶

class AWSLogsAsyncResponse(*args, **kwargs)¶

Bases: ModelNormal

A list of all Datadog-AWS logs integrations available in your Datadog organization.

Parameters:

errors ([AWSLogsAsyncError], optional) – List of errors.
status (str, optional) – Status of the properties.

aws_logs_lambda¶

class AWSLogsLambda(*args, **kwargs)¶

Bases: ModelNormal

Description of the Lambdas.

Parameters:: arn (str, optional) – Available ARN IDs.

aws_logs_list_response¶

class AWSLogsListResponse(*args, **kwargs)¶

Bases: ModelNormal

A list of all Datadog-AWS logs integrations available in your Datadog organization.

Parameters:

account_id (str, optional) – Your AWS Account ID without dashes.
lambdas ([AWSLogsLambda], optional) – List of ARNs configured in your Datadog account.
services ([str], optional) – Array of services IDs.

aws_logs_list_services_response¶

class AWSLogsListServicesResponse(*args, **kwargs)¶

Bases: ModelNormal

The list of current AWS services for which Datadog offers automatic log collection.

Parameters:

id (str, optional) – Key value in returned object.
label (str, optional) – Name of service available for configuration with Datadog logs.

aws_logs_services_request¶

class AWSLogsServicesRequest(*args, **kwargs)¶

Bases: ModelNormal

A list of current AWS services for which Datadog offers automatic log collection.

Parameters:

account_id (str) – Your AWS Account ID without dashes.
services ([str]) – Array of services IDs set to enable automatic log collection. Discover the list of available services with the get list of AWS log ready services API endpoint.

aws_namespace¶

class AWSNamespace(*args, **kwargs)¶

Bases: ModelSimple

The namespace associated with the tag filter entry.

Parameters:

value (str) – Must be one of [“elb”, “application_elb”, “sqs”, “rds”, “custom”, “network_elb”, “lambda”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

aws_tag_filter¶

class AWSTagFilter(*args, **kwargs)¶

Bases: ModelNormal

A tag filter.

Parameters:

namespace (AWSNamespace, optional) – The namespace associated with the tag filter entry.
tag_filter_str (str, optional) – The tag filter string.

aws_tag_filter_create_request¶

class AWSTagFilterCreateRequest(*args, **kwargs)¶

Bases: ModelNormal

The objects used to set an AWS tag filter.

Parameters:

account_id (str, optional) – Your AWS Account ID without dashes.
namespace (AWSNamespace, optional) – The namespace associated with the tag filter entry.
tag_filter_str (str, optional) – The tag filter string.

aws_tag_filter_delete_request¶

class AWSTagFilterDeleteRequest(*args, **kwargs)¶

Bases: ModelNormal

The objects used to delete an AWS tag filter entry.

Parameters:

account_id (str, optional) – The unique identifier of your AWS account.
namespace (AWSNamespace, optional) – The namespace associated with the tag filter entry.

aws_tag_filter_list_response¶

class AWSTagFilterListResponse(*args, **kwargs)¶

Bases: ModelNormal

An array of tag filter rules by namespace and tag filter string.

Parameters:: filters ([AWSTagFilter], optional) – An array of tag filters.

azure_account¶

class AzureAccount(*args, **kwargs)¶

Bases: ModelNormal

Datadog-Azure integrations configured for your organization.

Parameters:

app_service_plan_filters (str, optional) – Limit the Azure app service plans that are pulled into Datadog using tags. Only app service plans that match one of the defined tags are imported into Datadog.
automute (bool, optional) – Silence monitors for expected Azure VM shutdowns.
client_id (str, optional) – Your Azure web application ID.
client_secret (str, optional) – Your Azure web application secret key.
container_app_filters (str, optional) – Limit the Azure container apps that are pulled into Datadog using tags. Only container apps that match one of the defined tags are imported into Datadog.
cspm_enabled (bool, optional) – When enabled, Datadog’s Cloud Security Management product scans resource configurations monitored by this app registration. Note: This requires resource_collection_enabled to be set to true.
custom_metrics_enabled (bool, optional) – Enable custom metrics for your organization.
errors ([str], optional) – Errors in your configuration.
host_filters (str, optional) – Limit the Azure instances that are pulled into Datadog by using tags. Only hosts that match one of the defined tags are imported into Datadog.
new_client_id (str, optional) – Your New Azure web application ID.
new_tenant_name (str, optional) – Your New Azure Active Directory ID.
resource_collection_enabled (bool, optional) – When enabled, Datadog collects metadata and configuration info from cloud resources (compute instances, databases, load balancers, etc.) monitored by this app registration.
tenant_name (str, optional) – Your Azure Active Directory ID.

azure_account_list_response¶

class AzureAccountListResponse(*args, **kwargs)¶

Bases: ModelSimple

Accounts configured for your organization.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

cancel_downtimes_by_scope_request¶

class CancelDowntimesByScopeRequest(*args, **kwargs)¶

Bases: ModelNormal

Cancel downtimes according to scope.

Parameters:: scope (str) – The scope(s) to which the downtime applies and must be in key:value format. For example, host:app2. Provide multiple scopes as a comma-separated list like env:dev,env:prod. The resulting downtime applies to sources that matches ALL provided scopes ( env:dev AND env:prod ).

canceled_downtimes_ids¶

class CanceledDowntimesIds(*args, **kwargs)¶

Bases: ModelNormal

Object containing array of IDs of canceled downtimes.

Parameters:: cancelled_ids ([int], optional) – ID of downtimes that were canceled.

change_widget_definition¶

class ChangeWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The Change graph shows you the change in a value over the time period chosen.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
requests ([ChangeWidgetRequest]) –
Array of one request object to display in the widget.

See the dedicated Request JSON schema documentation
to learn how to build the REQUEST_SCHEMA.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (ChangeWidgetDefinitionType) – Type of the change widget.

change_widget_definition_type¶

class ChangeWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the change widget.

Parameters:

value (str) – If omitted defaults to “change”. Must be one of [“change”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

change_widget_request¶

class ChangeWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated change widget.

Parameters:

apm_query (LogQueryDefinition, optional) – The log query.
change_type (WidgetChangeType, optional) – Show the absolute or the relative change.
compare_to (WidgetCompareTo, optional) – Timeframe used for the change comparison.
event_query (LogQueryDefinition, optional) – The log query.
formulas ([WidgetFormula], optional) – List of formulas that operate on queries.
increase_good (bool, optional) – Whether to show increase as good.
log_query (LogQueryDefinition, optional) – The log query.
network_query (LogQueryDefinition, optional) – The log query.
order_by (WidgetOrderBy, optional) – What to order by.
order_dir (WidgetSort, optional) – Widget sorting methods.
process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.
profile_metrics_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – Query definition.
queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.
response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.
show_present (bool, optional) – Whether to show the present value.

check_can_delete_monitor_response¶

class CheckCanDeleteMonitorResponse(*args, **kwargs)¶

Bases: ModelNormal

Response of monitor IDs that can or can’t be safely deleted.

Parameters:

data (CheckCanDeleteMonitorResponseData) – Wrapper object with the list of monitor IDs.
errors ({str: ([str],)}, none_type, optional) – A mapping of Monitor ID to strings denoting where it’s used.

check_can_delete_monitor_response_data¶

class CheckCanDeleteMonitorResponseData(*args, **kwargs)¶

Bases: ModelNormal

Wrapper object with the list of monitor IDs.

Parameters:: ok ([int], optional) – An array of of Monitor IDs that can be safely deleted.

check_can_delete_slo_response¶

class CheckCanDeleteSLOResponse(*args, **kwargs)¶

Bases: ModelNormal

A service level objective response containing the requested object.

Parameters:

data (CheckCanDeleteSLOResponseData, optional) – An array of service level objective objects.
errors ({str: (str,)}, optional) – A mapping of SLO id to it’s current usages.

check_can_delete_slo_response_data¶

class CheckCanDeleteSLOResponseData(*args, **kwargs)¶

Bases: ModelNormal

An array of service level objective objects.

Parameters:: ok ([str], optional) – An array of of SLO IDs that can be safely deleted.

check_status_widget_definition¶

class CheckStatusWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

Check status shows the current status or number of results for any check performed.

Parameters:

check (str) – Name of the check to use in the widget.
group (str, optional) – Group reporting a single check.
group_by ([str], optional) – List of tag prefixes to group by in the case of a cluster check.
grouping (WidgetGrouping) – The kind of grouping to use.
tags ([str], optional) – List of tags used to filter the groups reporting a cluster check.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (CheckStatusWidgetDefinitionType) – Type of the check status widget.

check_status_widget_definition_type¶

class CheckStatusWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the check status widget.

Parameters:

value (str) – If omitted defaults to “check_status”. Must be one of [“check_status”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

content_encoding¶

class ContentEncoding(*args, **kwargs)¶

Bases: ModelSimple

HTTP header used to compress the media-type.

Parameters:

value (str) – Must be one of [“gzip”, “deflate”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

creator¶

class Creator(*args, **kwargs)¶

Bases: ModelNormal

Object describing the creator of the shared element.

Parameters:

email (str, optional) – Email of the creator.
handle (str, optional) – Handle of the creator.
name (str, none_type, optional) – Name of the creator.

dashboard¶

class Dashboard(*args, **kwargs)¶

Bases: ModelNormal

A dashboard is Datadog’s tool for visually tracking, analyzing, and displaying key performance metrics, which enable you to monitor the health of your infrastructure.

Parameters:

author_handle (str, optional) – Identifier of the dashboard author.
author_name (str, none_type, optional) – Name of the dashboard author.
created_at (datetime, optional) – Creation date of the dashboard.
description (str, none_type, optional) – Description of the dashboard.
id (str, optional) – ID of the dashboard.
is_read_only (bool, optional) –
Whether this dashboard is read-only. If True, only the author and admins can make changes to it.

This property is deprecated; please use the Restriction Policies API instead to manage write authorization for individual dashboards. Deprecated.
layout_type (DashboardLayoutType) – Layout type of the dashboard.
modified_at (datetime, optional) – Modification date of the dashboard.
notify_list ([str], none_type, optional) – List of handles of users to notify when changes are made to this dashboard.
reflow_type (DashboardReflowType, optional) – Reflow type for a new dashboard layout dashboard. Set this only when layout type is ‘ordered’. If set to ‘fixed’, the dashboard expects all widgets to have a layout, and if it’s set to ‘auto’, widgets should not have layouts.
restricted_roles ([str], optional) –
A list of role identifiers. Only the author and users associated with at least one of these roles can edit this dashboard.

This property is deprecated; please use the Restriction Policies API instead to manage write authorization for individual dashboards. Deprecated.
tags ([str], none_type, optional) – List of team names representing ownership of a dashboard.
template_variable_presets ([DashboardTemplateVariablePreset], none_type, optional) – Array of template variables saved views.
template_variables ([DashboardTemplateVariable], none_type, optional) – List of template variables for this dashboard.
title (str) – Title of the dashboard.
url (str, optional) – The URL of the dashboard.
widgets ([Widget]) – List of widgets to display on the dashboard.

dashboard_bulk_action_data¶

class DashboardBulkActionData(*args, **kwargs)¶

Bases: ModelNormal

Dashboard bulk action request data.

Parameters:

id (str) – Dashboard resource ID.
type (DashboardResourceType) – Dashboard resource type.

dashboard_bulk_action_data_list¶

class DashboardBulkActionDataList(*args, **kwargs)¶

Bases: ModelSimple

List of dashboard bulk action request data objects.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

dashboard_bulk_delete_request¶

class DashboardBulkDeleteRequest(*args, **kwargs)¶

Bases: ModelNormal

Dashboard bulk delete request body.

Parameters:: data (DashboardBulkActionDataList) – List of dashboard bulk action request data objects.

dashboard_delete_response¶

class DashboardDeleteResponse(*args, **kwargs)¶

Bases: ModelNormal

Response from the delete dashboard call.

Parameters:: deleted_dashboard_id (str, optional) – ID of the deleted dashboard.

dashboard_global_time¶

class DashboardGlobalTime(*args, **kwargs)¶

Bases: ModelNormal

Object containing the live span selection for the dashboard.

Parameters:: live_span (DashboardGlobalTimeLiveSpan, optional) – Dashboard global time live_span selection

dashboard_global_time_live_span¶

class DashboardGlobalTimeLiveSpan(*args, **kwargs)¶

Bases: ModelSimple

Dashboard global time live_span selection

Parameters:

value (str) – Must be one of [“15m”, “1h”, “4h”, “1d”, “2d”, “1w”, “1mo”, “3mo”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

dashboard_invite_type¶

class DashboardInviteType(*args, **kwargs)¶

Bases: ModelSimple

Type for shared dashboard invitation request body.

Parameters:

value (str) – If omitted defaults to “public_dashboard_invitation”. Must be one of [“public_dashboard_invitation”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

dashboard_layout_type¶

class DashboardLayoutType(*args, **kwargs)¶

Bases: ModelSimple

Layout type of the dashboard.

Parameters:

value (str) – Must be one of [“ordered”, “free”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

dashboard_list¶

class DashboardList(*args, **kwargs)¶

Bases: ModelNormal

Your Datadog Dashboards.

Parameters:

author (Creator, optional) – Object describing the creator of the shared element.
created (datetime, optional) – Date of creation of the dashboard list.
dashboard_count (int, optional) – The number of dashboards in the list.
id (int, optional) – The ID of the dashboard list.
is_favorite (bool, optional) – Whether or not the list is in the favorites.
modified (datetime, optional) – Date of last edition of the dashboard list.
name (str) – The name of the dashboard list.
type (str, optional) – The type of dashboard list.

dashboard_list_delete_response¶

class DashboardListDeleteResponse(*args, **kwargs)¶

Bases: ModelNormal

Deleted dashboard details.

Parameters:: deleted_dashboard_list_id (int, optional) – ID of the deleted dashboard list.

dashboard_list_list_response¶

class DashboardListListResponse(*args, **kwargs)¶

Bases: ModelNormal

Information on your dashboard lists.

Parameters:: dashboard_lists ([DashboardList], optional) – List of all your dashboard lists.

dashboard_reflow_type¶

class DashboardReflowType(*args, **kwargs)¶

Bases: ModelSimple

Reflow type for a new dashboard layout dashboard. Set this only when layout type is ‘ordered’.: If set to ‘fixed’, the dashboard expects all widgets to have a layout, and if it’s set to ‘auto’, widgets should not have layouts.

Parameters:

value (str) – Must be one of [“auto”, “fixed”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

dashboard_resource_type¶

class DashboardResourceType(*args, **kwargs)¶

Bases: ModelSimple

Dashboard resource type.

Parameters:

value (str) – If omitted defaults to “dashboard”. Must be one of [“dashboard”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

dashboard_restore_request¶

class DashboardRestoreRequest(*args, **kwargs)¶

Bases: ModelNormal

Dashboard restore request body.

Parameters:: data (DashboardBulkActionDataList) – List of dashboard bulk action request data objects.

dashboard_share_type¶

class DashboardShareType(*args, **kwargs)¶

Bases: ModelSimple

Type of sharing access (either open to anyone who has the public URL or invite-only).

Parameters:

value (str) – Must be one of [“open”, “invite”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

dashboard_summary¶

class DashboardSummary(*args, **kwargs)¶

Bases: ModelNormal

Dashboard summary response.

Parameters:: dashboards ([DashboardSummaryDefinition], optional) – List of dashboard definitions.

dashboard_summary_definition¶

class DashboardSummaryDefinition(*args, **kwargs)¶

Bases: ModelNormal

Dashboard definition.

Parameters:

author_handle (str, optional) – Identifier of the dashboard author.
created_at (datetime, optional) – Creation date of the dashboard.
description (str, none_type, optional) – Description of the dashboard.
id (str, optional) – Dashboard identifier.
is_read_only (bool, optional) –
Whether this dashboard is read-only. If True, only the author and admins can make changes to it.

This property is deprecated; please use the Restriction Policies API instead to manage write authorization for individual dashboards. Deprecated.
layout_type (DashboardLayoutType, optional) – Layout type of the dashboard.
modified_at (datetime, optional) – Modification date of the dashboard.
title (str, optional) – Title of the dashboard.
url (str, optional) – URL of the dashboard.

dashboard_template_variable¶

class DashboardTemplateVariable(*args, **kwargs)¶

Bases: ModelNormal

Template variable.

Parameters:

available_values ([str], none_type, optional) – The list of values that the template variable drop-down is limited to.
default (str, none_type, optional) – (deprecated) The default value for the template variable on dashboard load. Cannot be used in conjunction with defaults. Deprecated.
defaults ([str], optional) – One or many default values for template variables on load. If more than one default is specified, they will be unioned together with OR. Cannot be used in conjunction with default.
name (str) – The name of the variable.
prefix (str, none_type, optional) – The tag prefix associated with the variable. Only tags with this prefix appear in the variable drop-down.

dashboard_template_variable_preset¶

class DashboardTemplateVariablePreset(*args, **kwargs)¶

Bases: ModelNormal

Template variables saved views.

Parameters:

name (str, optional) – The name of the variable.
template_variables ([DashboardTemplateVariablePresetValue], optional) – List of variables.

dashboard_template_variable_preset_value¶

class DashboardTemplateVariablePresetValue(*args, **kwargs)¶

Bases: ModelNormal

Template variables saved views.

Parameters:

name (str, optional) – The name of the variable.
value (str, optional) – (deprecated) The value of the template variable within the saved view. Cannot be used in conjunction with values. Deprecated.
values ([str], optional) – One or many template variable values within the saved view, which will be unioned together using OR if more than one is specified. Cannot be used in conjunction with value.

dashboard_type¶

class DashboardType(*args, **kwargs)¶

Bases: ModelSimple

The type of the associated private dashboard.

Parameters:

value (str) – Must be one of [“custom_timeboard”, “custom_screenboard”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

delete_shared_dashboard_response¶

class DeleteSharedDashboardResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing token of deleted shared dashboard.

Parameters:: deleted_public_dashboard_token (str, optional) – Token associated with the shared dashboard that was revoked.

deleted_monitor¶

class DeletedMonitor(*args, **kwargs)¶

Bases: ModelNormal

Response from the delete monitor call.

Parameters:: deleted_monitor_id (int, optional) – ID of the deleted monitor.

distribution_point¶

class DistributionPoint(*args, **kwargs)¶

Bases: ModelSimple

Array of distribution points.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

distribution_points_content_encoding¶

class DistributionPointsContentEncoding(*args, **kwargs)¶

Bases: ModelSimple

HTTP header used to compress the media-type.

Parameters:

value (str) – If omitted defaults to “deflate”. Must be one of [“deflate”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

distribution_points_payload¶

class DistributionPointsPayload(*args, **kwargs)¶

Bases: ModelNormal

The distribution points payload.

Parameters:: series ([DistributionPointsSeries]) – A list of distribution points series to submit to Datadog.

distribution_points_series¶

class DistributionPointsSeries(*args, **kwargs)¶

Bases: ModelNormal

A distribution points metric to submit to Datadog.

Parameters:

host (str, optional) – The name of the host that produced the distribution point metric.
metric (str) – The name of the distribution points metric.
points ([DistributionPoint]) – Points relating to the distribution point metric. All points must be tuples with timestamp and a list of values (cannot be a string). Timestamps should be in POSIX time in seconds.
tags ([str], optional) – A list of tags associated with the distribution point metric.
type (DistributionPointsType, optional) – The type of the distribution point.

distribution_points_type¶

class DistributionPointsType(*args, **kwargs)¶

Bases: ModelSimple

The type of the distribution point.

Parameters:

value (str) – If omitted defaults to “distribution”. Must be one of [“distribution”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

distribution_widget_definition¶

class DistributionWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The Distribution visualization is another way of showing metrics aggregated across one or several tags, such as hosts. Unlike the heat map, a distribution graph’s x-axis is quantity rather than time.

Parameters:

custom_links ([WidgetCustomLink], optional) – A list of custom links.
legend_size (str, optional) – (Deprecated) The widget legend was replaced by a tooltip and sidebar. Deprecated.
markers ([WidgetMarker], optional) – List of markers.
requests ([DistributionWidgetRequest]) –
Array of one request object to display in the widget.

See the dedicated Request JSON schema documentation
to learn how to build the REQUEST_SCHEMA.
show_legend (bool, optional) – (Deprecated) The widget legend was replaced by a tooltip and sidebar. Deprecated.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (DistributionWidgetDefinitionType) – Type of the distribution widget.
xaxis (DistributionWidgetXAxis, optional) – X Axis controls for the distribution widget.
yaxis (DistributionWidgetYAxis, optional) – Y Axis controls for the distribution widget.

distribution_widget_definition_type¶

class DistributionWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the distribution widget.

Parameters:

value (str) – If omitted defaults to “distribution”. Must be one of [“distribution”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

distribution_widget_histogram_request_query¶

class DistributionWidgetHistogramRequestQuery(*args, **kwargs)¶

Bases: ModelComposed

Query definition for Distribution Widget Histogram Request

Parameters:

aggregator (FormulaAndFunctionMetricAggregation, optional) – The aggregation methods available for metrics queries.
data_source (FormulaAndFunctionMetricDataSource) – Data source for metrics queries.
name (str) – Name of the query for use in formulas.
query (str) – Metrics query definition.
compute (FormulaAndFunctionEventQueryDefinitionCompute) – Compute options.
group_by ([FormulaAndFunctionEventQueryGroupBy], optional) – Group by options.
indexes ([str], optional) – An array of index names to query in the stream. Omit or use [] to query all indexes at once.
search (FormulaAndFunctionEventQueryDefinitionSearch, optional) – Search options.
storage (str, optional) – Option for storage location. Feature in Private Beta.
env (str) – APM environment.
operation_name (str, optional) – Name of operation on service.
primary_tag_name (str, optional) – Name of the second primary tag used within APM. Required when primary_tag_value is specified. See https://docs.datadoghq.com/tracing/guide/setting_primary_tags_to_scope/#add-a-second-primary-tag-in-datadog
primary_tag_value (str, optional) – Value of the second primary tag by which to filter APM data. primary_tag_name must also be specified.
resource_name (str, optional) – APM resource name.
service (str) – APM service name.
stat (FormulaAndFunctionApmResourceStatName) – APM resource stat name.

distribution_widget_histogram_request_type¶

class DistributionWidgetHistogramRequestType(*args, **kwargs)¶

Bases: ModelSimple

Request type for the histogram request.

Parameters:

value (str) – If omitted defaults to “histogram”. Must be one of [“histogram”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

distribution_widget_request¶

class DistributionWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated distribution widget.

Parameters:

apm_query (LogQueryDefinition, optional) – The log query.
apm_stats_query (ApmStatsQueryDefinition, optional) – The APM stats query for table and distributions widgets.
event_query (LogQueryDefinition, optional) – The log query.
log_query (LogQueryDefinition, optional) – The log query.
network_query (LogQueryDefinition, optional) – The log query.
process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.
profile_metrics_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – Widget query.
query (DistributionWidgetHistogramRequestQuery, optional) – Query definition for Distribution Widget Histogram Request
request_type (DistributionWidgetHistogramRequestType, optional) – Request type for the histogram request.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.
style (WidgetStyle, optional) – Widget style definition.

distribution_widget_x_axis¶

class DistributionWidgetXAxis(*args, **kwargs)¶

Bases: ModelNormal

X Axis controls for the distribution widget.

Parameters:

include_zero (bool, optional) – True includes zero.
max (str, optional) – Specifies maximum value to show on the x-axis. It takes a number, percentile (p90 === 90th percentile), or auto for default behavior.
min (str, optional) – Specifies minimum value to show on the x-axis. It takes a number, percentile (p90 === 90th percentile), or auto for default behavior.
scale (str, optional) – Specifies the scale type. Possible values are linear.

distribution_widget_y_axis¶

class DistributionWidgetYAxis(*args, **kwargs)¶

Bases: ModelNormal

Y Axis controls for the distribution widget.

Parameters:

include_zero (bool, optional) – True includes zero.
label (str, optional) – The label of the axis to display on the graph.
max (str, optional) – Specifies the maximum value to show on the y-axis. It takes a number, or auto for default behavior.
min (str, optional) – Specifies minimum value to show on the y-axis. It takes a number, or auto for default behavior.
scale (str, optional) – Specifies the scale type. Possible values are linear or log.

downtime¶

class Downtime(*args, **kwargs)¶

Bases: ModelNormal

Downtiming gives you greater control over monitor notifications by allowing you to globally exclude scopes from alerting. Downtime settings, which can be scheduled with start and end times, prevent all alerting related to specified Datadog tags.

Parameters:

active (bool, optional) – If a scheduled downtime currently exists.
active_child (DowntimeChild, none_type, optional) – The downtime object definition of the active child for the original parent recurring downtime. This field will only exist on recurring downtimes.
canceled (int, none_type, optional) – If a scheduled downtime is canceled.
creator_id (int, optional) – User ID of the downtime creator.
disabled (bool, optional) – If a downtime has been disabled.
downtime_type (int, optional) – 0 for a downtime applied on * or all, 1 when the downtime is only scoped to hosts, or 2 when the downtime is scoped to anything but hosts.
end (int, none_type, optional) – POSIX timestamp to end the downtime. If not provided, the downtime is in effect indefinitely until you cancel it.
id (int, optional) – The downtime ID.
message (str, none_type, optional) – A message to include with notifications for this downtime. Email notifications can be sent to specific users by using the same @username notation as events.
monitor_id (int, none_type, optional) – A single monitor to which the downtime applies. If not provided, the downtime applies to all monitors.
monitor_tags ([str], optional) – A comma-separated list of monitor tags. For example, tags that are applied directly to monitors, not tags that are used in monitor queries (which are filtered by the scope parameter), to which the downtime applies. The resulting downtime applies to monitors that match ALL provided monitor tags. For example, service:postgres AND team:frontend.
mute_first_recovery_notification (bool, optional) – If the first recovery notification during a downtime should be muted.
notify_end_states ([NotifyEndState], optional) – States for which notify_end_types sends out notifications for.
notify_end_types ([NotifyEndType], optional) – If set, notifies if a monitor is in an alert-worthy state ( ALERT , WARNING , or NO DATA ) when this downtime expires or is canceled. Applied to monitors that change states during the downtime (such as from OK to ALERT , WARNING , or NO DATA ), and to monitors that already have an alert-worthy state when downtime begins.
parent_id (int, none_type, optional) – ID of the parent Downtime.
recurrence (DowntimeRecurrence, none_type, optional) – An object defining the recurrence of the downtime.
scope ([str], optional) – The scope(s) to which the downtime applies and must be in key:value format. For example, host:app2. Provide multiple scopes as a comma-separated list like env:dev,env:prod. The resulting downtime applies to sources that matches ALL provided scopes ( env:dev AND env:prod ).
start (int, optional) – POSIX timestamp to start the downtime. If not provided, the downtime starts the moment it is created.
timezone (str, optional) – The timezone in which to display the downtime’s start and end times in Datadog applications.
updater_id (int, none_type, optional) – ID of the last user that updated the downtime.

downtime_child¶

class DowntimeChild(*args, **kwargs)¶

Bases: ModelNormal

The downtime object definition of the active child for the original parent recurring downtime. This field will only exist on recurring downtimes.

Parameters:

active (bool, optional) – If a scheduled downtime currently exists.
canceled (int, none_type, optional) – If a scheduled downtime is canceled.
creator_id (int, optional) – User ID of the downtime creator.
disabled (bool, optional) – If a downtime has been disabled.
downtime_type (int, optional) – 0 for a downtime applied on * or all, 1 when the downtime is only scoped to hosts, or 2 when the downtime is scoped to anything but hosts.
end (int, none_type, optional) – POSIX timestamp to end the downtime. If not provided, the downtime is in effect indefinitely until you cancel it.
id (int, optional) – The downtime ID.
message (str, none_type, optional) – A message to include with notifications for this downtime. Email notifications can be sent to specific users by using the same @username notation as events.
monitor_id (int, none_type, optional) – A single monitor to which the downtime applies. If not provided, the downtime applies to all monitors.
monitor_tags ([str], optional) – A comma-separated list of monitor tags. For example, tags that are applied directly to monitors, not tags that are used in monitor queries (which are filtered by the scope parameter), to which the downtime applies. The resulting downtime applies to monitors that match ALL provided monitor tags. For example, service:postgres AND team:frontend.
mute_first_recovery_notification (bool, optional) – If the first recovery notification during a downtime should be muted.
notify_end_states ([NotifyEndState], optional) – States for which notify_end_types sends out notifications for.
notify_end_types ([NotifyEndType], optional) – If set, notifies if a monitor is in an alert-worthy state ( ALERT , WARNING , or NO DATA ) when this downtime expires or is canceled. Applied to monitors that change states during the downtime (such as from OK to ALERT , WARNING , or NO DATA ), and to monitors that already have an alert-worthy state when downtime begins.
parent_id (int, none_type, optional) – ID of the parent Downtime.
recurrence (DowntimeRecurrence, none_type, optional) – An object defining the recurrence of the downtime.
scope ([str], optional) – The scope(s) to which the downtime applies and must be in key:value format. For example, host:app2. Provide multiple scopes as a comma-separated list like env:dev,env:prod. The resulting downtime applies to sources that matches ALL provided scopes ( env:dev AND env:prod ).
start (int, optional) – POSIX timestamp to start the downtime. If not provided, the downtime starts the moment it is created.
timezone (str, optional) – The timezone in which to display the downtime’s start and end times in Datadog applications.
updater_id (int, none_type, optional) – ID of the last user that updated the downtime.

downtime_recurrence¶

class DowntimeRecurrence(*args, **kwargs)¶

Bases: ModelNormal

An object defining the recurrence of the downtime.

Parameters:

period (int, optional) – How often to repeat as an integer. For example, to repeat every 3 days, select a type of days and a period of 3.
rrule (str, optional) –
The RRULE standard for defining recurring events ( requires to set “type” to rrule ) For example, to have a recurring event on the first day of each month, set the type to rrule and set the FREQ to MONTHLY and BYMONTHDAY to 1. Most common rrule options from the iCalendar Spec are supported.

Note : Attributes specifying the duration in RRULE are not supported (for example, DTSTART , DTEND , DURATION ). More examples available in this downtime guide
type (str, optional) – The type of recurrence. Choose from days , weeks , months , years , rrule.
until_date (int, none_type, optional) – The date at which the recurrence should end as a POSIX timestamp. until_occurences and until_date are mutually exclusive.
until_occurrences (int, none_type, optional) – How many times the downtime is rescheduled. until_occurences and until_date are mutually exclusive.
week_days ([str], none_type, optional) – A list of week days to repeat on. Choose from Mon , Tue , Wed , Thu , Fri , Sat or Sun. Only applicable when type is weeks. First letter must be capitalized.

event¶

class Event(*args, **kwargs)¶

Bases: ModelNormal

Object representing an event.

Parameters:

alert_type (EventAlertType, optional) – If an alert event is enabled, set its type. For example, error , warning , info , success , user_update , recommendation , and snapshot.
date_happened (int, optional) – POSIX timestamp of the event. Must be sent as an integer (that is no quotes). Limited to events no older than 18 hours.
device_name (str, optional) – A device name.
host (str, optional) – Host name to associate with the event. Any tags associated with the host are also applied to this event.
id (int, optional) – Integer ID of the event.
id_str (str, optional) – Handling IDs as large 64-bit numbers can cause loss of accuracy issues with some programming languages. Instead, use the string representation of the Event ID to avoid losing accuracy.
payload (str, optional) – Payload of the event.
priority (EventPriority, none_type, optional) – The priority of the event. For example, normal or low.
source_type_name (str, optional) – The type of event being posted. Option examples include nagios, hudson, jenkins, my_apps, chef, puppet, git, bitbucket, etc. The list of standard source attribute values available here.
tags ([str], optional) – A list of tags to apply to the event.
text (str, optional) – The body of the event. Limited to 4000 characters. The text supports markdown. To use markdown in the event text, start the text block with %%% \n and end the text block with \n %%%. Use msg_text with the Datadog Ruby library.
title (str, optional) – The event title.
url (str, optional) – URL of the event.

event_alert_type¶

class EventAlertType(*args, **kwargs)¶

Bases: ModelSimple

If an alert event is enabled, set its type.: For example, error, warning, info, success, user_update, recommendation, and snapshot.

Parameters:

value (str) – Must be one of [“error”, “warning”, “info”, “success”, “user_update”, “recommendation”, “snapshot”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

event_create_request¶

class EventCreateRequest(*args, **kwargs)¶

Bases: ModelNormal

Object representing an event.

Parameters:

aggregation_key (str, optional) – An arbitrary string to use for aggregation. Limited to 100 characters. If you specify a key, all events using that key are grouped together in the Event Stream.
alert_type (EventAlertType, optional) – If an alert event is enabled, set its type. For example, error , warning , info , success , user_update , recommendation , and snapshot.
date_happened (int, optional) – POSIX timestamp of the event. Must be sent as an integer (that is no quotes). Limited to events no older than 18 hours
device_name (str, optional) – A device name.
host (str, optional) – Host name to associate with the event. Any tags associated with the host are also applied to this event.
priority (EventPriority, none_type, optional) – The priority of the event. For example, normal or low.
related_event_id (int, optional) – ID of the parent event. Must be sent as an integer (that is no quotes).
source_type_name (str, optional) –
The type of event being posted. Option examples include nagios, hudson, jenkins, my_apps, chef, puppet, git, bitbucket, etc. A complete list of source attribute values available here.
tags ([str], optional) – A list of tags to apply to the event.
text (str) – The body of the event. Limited to 4000 characters. The text supports markdown. To use markdown in the event text, start the text block with %%% \n and end the text block with \n %%%. Use msg_text with the Datadog Ruby library.
title (str) – The event title.

event_create_response¶

class EventCreateResponse(*args, **kwargs)¶

Bases: ModelNormal

Object containing an event response.

Parameters:

event (Event, optional) – Object representing an event.
status (str, optional) – A status.

event_list_response¶

class EventListResponse(*args, **kwargs)¶

Bases: ModelNormal

An event list response.

Parameters:

events ([Event], optional) – An array of events.
status (str, optional) – A status.

event_priority¶

class EventPriority(*args, **kwargs)¶

Bases: ModelSimple

The priority of the event. For example, normal or low.

Parameters:

value (str) – Must be one of [“normal”, “low”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

event_query_definition¶

class EventQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

The event query.

Parameters:

search (str) – The query being made on the event.
tags_execution (str) – The execution method for multi-value filters. Can be either and or or.

event_response¶

class EventResponse(*args, **kwargs)¶

Bases: ModelNormal

Object containing an event response.

Parameters:

event (Event, optional) – Object representing an event.
status (str, optional) – A status.

event_stream_widget_definition¶

class EventStreamWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The event stream is a widget version of the stream of events on the Event Stream view. Only available on FREE layout dashboards.

Parameters:

event_size (WidgetEventSize, optional) – Size to use to display an event.
query (str) – Query to filter the event stream with.
tags_execution (str, optional) – The execution method for multi-value filters. Can be either and or or.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (EventStreamWidgetDefinitionType) – Type of the event stream widget.

event_stream_widget_definition_type¶

class EventStreamWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the event stream widget.

Parameters:

value (str) – If omitted defaults to “event_stream”. Must be one of [“event_stream”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

event_timeline_widget_definition¶

class EventTimelineWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The event timeline is a widget version of the timeline that appears at the top of the Event Stream view. Only available on FREE layout dashboards.

Parameters:

query (str) – Query to filter the event timeline with.
tags_execution (str, optional) – The execution method for multi-value filters. Can be either and or or.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (EventTimelineWidgetDefinitionType) – Type of the event timeline widget.

event_timeline_widget_definition_type¶

class EventTimelineWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the event timeline widget.

Parameters:

value (str) – If omitted defaults to “event_timeline”. Must be one of [“event_timeline”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_apm_dependency_stat_name¶

class FormulaAndFunctionApmDependencyStatName(*args, **kwargs)¶

Bases: ModelSimple

APM statistic.

Parameters:

value (str) – Must be one of [“avg_duration”, “avg_root_duration”, “avg_spans_per_trace”, “error_rate”, “pct_exec_time”, “pct_of_traces”, “total_traces_count”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_apm_dependency_stats_data_source¶

class FormulaAndFunctionApmDependencyStatsDataSource(*args, **kwargs)¶

Bases: ModelSimple

Data source for APM dependency stats queries.

Parameters:

value (str) – If omitted defaults to “apm_dependency_stats”. Must be one of [“apm_dependency_stats”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_apm_dependency_stats_query_definition¶

class FormulaAndFunctionApmDependencyStatsQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

A formula and functions APM dependency stats query.

Parameters:

data_source (FormulaAndFunctionApmDependencyStatsDataSource) – Data source for APM dependency stats queries.
env (str) – APM environment.
is_upstream (bool, optional) – Determines whether stats for upstream or downstream dependencies should be queried.
name (str) – Name of query to use in formulas.
operation_name (str) – Name of operation on service.
primary_tag_name (str, optional) – The name of the second primary tag used within APM; required when primary_tag_value is specified. See https://docs.datadoghq.com/tracing/guide/setting_primary_tags_to_scope/#add-a-second-primary-tag-in-datadog.
primary_tag_value (str, optional) – Filter APM data by the second primary tag. primary_tag_name must also be specified.
resource_name (str) – APM resource.
service (str) – APM service.
stat (FormulaAndFunctionApmDependencyStatName) – APM statistic.

formula_and_function_apm_resource_stat_name¶

class FormulaAndFunctionApmResourceStatName(*args, **kwargs)¶

Bases: ModelSimple

APM resource stat name.

Parameters:

value (str) – Must be one of [“errors”, “error_rate”, “hits”, “latency_avg”, “latency_distribution”, “latency_max”, “latency_p50”, “latency_p75”, “latency_p90”, “latency_p95”, “latency_p99”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_apm_resource_stats_data_source¶

class FormulaAndFunctionApmResourceStatsDataSource(*args, **kwargs)¶

Bases: ModelSimple

Data source for APM resource stats queries.

Parameters:

value (str) – If omitted defaults to “apm_resource_stats”. Must be one of [“apm_resource_stats”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_apm_resource_stats_query_definition¶

class FormulaAndFunctionApmResourceStatsQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

APM resource stats query using formulas and functions.

Parameters:

data_source (FormulaAndFunctionApmResourceStatsDataSource) – Data source for APM resource stats queries.
env (str) – APM environment.
group_by ([str], optional) – Array of fields to group results by.
name (str) – Name of this query to use in formulas.
operation_name (str, optional) – Name of operation on service.
primary_tag_name (str, optional) – Name of the second primary tag used within APM. Required when primary_tag_value is specified. See https://docs.datadoghq.com/tracing/guide/setting_primary_tags_to_scope/#add-a-second-primary-tag-in-datadog
primary_tag_value (str, optional) – Value of the second primary tag by which to filter APM data. primary_tag_name must also be specified.
resource_name (str, optional) – APM resource name.
service (str) – APM service name.
stat (FormulaAndFunctionApmResourceStatName) – APM resource stat name.

formula_and_function_cloud_cost_data_source¶

class FormulaAndFunctionCloudCostDataSource(*args, **kwargs)¶

Bases: ModelSimple

Data source for Cloud Cost queries.

Parameters:

value (str) – If omitted defaults to “cloud_cost”. Must be one of [“cloud_cost”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_cloud_cost_query_definition¶

class FormulaAndFunctionCloudCostQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

A formula and functions Cloud Cost query.

Parameters:

aggregator (WidgetAggregator, optional) – Aggregator used for the request.
data_source (FormulaAndFunctionCloudCostDataSource) – Data source for Cloud Cost queries.
name (str) – Name of the query for use in formulas.
query (str) – Query for Cloud Cost data.

formula_and_function_event_aggregation¶

class FormulaAndFunctionEventAggregation(*args, **kwargs)¶

Bases: ModelSimple

Aggregation methods for event platform queries.

Parameters:

value (str) – Must be one of [“count”, “cardinality”, “median”, “pc75”, “pc90”, “pc95”, “pc98”, “pc99”, “sum”, “min”, “max”, “avg”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_event_query_definition¶

class FormulaAndFunctionEventQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

A formula and functions events query.

Parameters:

compute (FormulaAndFunctionEventQueryDefinitionCompute) – Compute options.
data_source (FormulaAndFunctionEventsDataSource) – Data source for event platform-based queries.
group_by ([FormulaAndFunctionEventQueryGroupBy], optional) – Group by options.
indexes ([str], optional) – An array of index names to query in the stream. Omit or use [] to query all indexes at once.
name (str) – Name of the query for use in formulas.
search (FormulaAndFunctionEventQueryDefinitionSearch, optional) – Search options.
storage (str, optional) – Option for storage location. Feature in Private Beta.

formula_and_function_event_query_definition_compute¶

class FormulaAndFunctionEventQueryDefinitionCompute(*args, **kwargs)¶

Bases: ModelNormal

Compute options.

Parameters:

aggregation (FormulaAndFunctionEventAggregation) – Aggregation methods for event platform queries.
interval (int, optional) – A time interval in milliseconds.
metric (str, optional) – Measurable attribute to compute.

formula_and_function_event_query_definition_search¶

class FormulaAndFunctionEventQueryDefinitionSearch(*args, **kwargs)¶

Bases: ModelNormal

Search options.

Parameters:: query (str) – Events search string.

formula_and_function_event_query_group_by¶

class FormulaAndFunctionEventQueryGroupBy(*args, **kwargs)¶

Bases: ModelNormal

List of objects used to group by.

Parameters:

facet (str) – Event facet.
limit (int, optional) – Number of groups to return.
sort (FormulaAndFunctionEventQueryGroupBySort, optional) – Options for sorting group by results.

formula_and_function_event_query_group_by_sort¶

class FormulaAndFunctionEventQueryGroupBySort(*args, **kwargs)¶

Bases: ModelNormal

Options for sorting group by results.

Parameters:

aggregation (FormulaAndFunctionEventAggregation) – Aggregation methods for event platform queries.
metric (str, optional) – Metric used for sorting group by results.
order (QuerySortOrder, optional) – Direction of sort.

formula_and_function_events_data_source¶

class FormulaAndFunctionEventsDataSource(*args, **kwargs)¶

Bases: ModelSimple

Data source for event platform-based queries.

Parameters:

value (str) – Must be one of [“logs”, “spans”, “network”, “rum”, “security_signals”, “profiles”, “audit”, “events”, “ci_tests”, “ci_pipelines”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_metric_aggregation¶

class FormulaAndFunctionMetricAggregation(*args, **kwargs)¶

Bases: ModelSimple

The aggregation methods available for metrics queries.

Parameters:

value (str) – Must be one of [“avg”, “min”, “max”, “sum”, “last”, “area”, “l2norm”, “percentile”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_metric_data_source¶

class FormulaAndFunctionMetricDataSource(*args, **kwargs)¶

Bases: ModelSimple

Data source for metrics queries.

Parameters:

value (str) – If omitted defaults to “metrics”. Must be one of [“metrics”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_metric_query_definition¶

class FormulaAndFunctionMetricQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

A formula and functions metrics query.

Parameters:

aggregator (FormulaAndFunctionMetricAggregation, optional) – The aggregation methods available for metrics queries.
data_source (FormulaAndFunctionMetricDataSource) – Data source for metrics queries.
name (str) – Name of the query for use in formulas.
query (str) – Metrics query definition.

formula_and_function_process_query_data_source¶

class FormulaAndFunctionProcessQueryDataSource(*args, **kwargs)¶

Bases: ModelSimple

Data sources that rely on the process backend.

Parameters:

value (str) – Must be one of [“process”, “container”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_process_query_definition¶

class FormulaAndFunctionProcessQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

Process query using formulas and functions.

Parameters:

aggregator (FormulaAndFunctionMetricAggregation, optional) – The aggregation methods available for metrics queries.
data_source (FormulaAndFunctionProcessQueryDataSource) – Data sources that rely on the process backend.
is_normalized_cpu (bool, optional) – Whether to normalize the CPU percentages.
limit (int, optional) – Number of hits to return.
metric (str) – Process metric name.
name (str) – Name of query for use in formulas.
sort (QuerySortOrder, optional) – Direction of sort.
tag_filters ([str], optional) – An array of tags to filter by.
text_filter (str, optional) – Text to use as filter.

formula_and_function_query_definition¶

class FormulaAndFunctionQueryDefinition(*args, **kwargs)¶

Bases: ModelComposed

A formula and function query.

Parameters:

aggregator (FormulaAndFunctionMetricAggregation, optional) – The aggregation methods available for metrics queries.
data_source (FormulaAndFunctionMetricDataSource) – Data source for metrics queries.
name (str) – Name of the query for use in formulas.
query (str) – Metrics query definition.
compute (FormulaAndFunctionEventQueryDefinitionCompute) – Compute options.
group_by ([FormulaAndFunctionEventQueryGroupBy], optional) – Group by options.
indexes ([str], optional) – An array of index names to query in the stream. Omit or use [] to query all indexes at once.
search (FormulaAndFunctionEventQueryDefinitionSearch, optional) – Search options.
storage (str, optional) – Option for storage location. Feature in Private Beta.
is_normalized_cpu (bool, optional) – Whether to normalize the CPU percentages.
limit (int, optional) – Number of hits to return.
metric (str) – Process metric name.
sort (QuerySortOrder, optional) – Direction of sort.
tag_filters ([str], optional) – An array of tags to filter by.
text_filter (str, optional) – Text to use as filter.
env (str) – APM environment.
is_upstream (bool, optional) – Determines whether stats for upstream or downstream dependencies should be queried.
operation_name (str) – Name of operation on service.
primary_tag_name (str, optional) – The name of the second primary tag used within APM; required when primary_tag_value is specified. See https://docs.datadoghq.com/tracing/guide/setting_primary_tags_to_scope/#add-a-second-primary-tag-in-datadog.
primary_tag_value (str, optional) – Filter APM data by the second primary tag. primary_tag_name must also be specified.
resource_name (str) – APM resource.
service (str) – APM service.
stat (FormulaAndFunctionApmDependencyStatName) – APM statistic.
additional_query_filters (str, optional) – Additional filters applied to the SLO query.
group_mode (FormulaAndFunctionSLOGroupMode, optional) – Group mode to query measures.
measure (FormulaAndFunctionSLOMeasure) – SLO measures queries.
slo_id (str) – ID of an SLO to query measures.
slo_query_type (FormulaAndFunctionSLOQueryType, optional) – Name of the query for use in formulas.

formula_and_function_response_format¶

class FormulaAndFunctionResponseFormat(*args, **kwargs)¶

Bases: ModelSimple

Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

Parameters:

value (str) – Must be one of [“timeseries”, “scalar”, “event_list”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_slo_data_source¶

class FormulaAndFunctionSLODataSource(*args, **kwargs)¶

Bases: ModelSimple

Data source for SLO measures queries.

Parameters:

value (str) – If omitted defaults to “slo”. Must be one of [“slo”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_slo_group_mode¶

class FormulaAndFunctionSLOGroupMode(*args, **kwargs)¶

Bases: ModelSimple

Group mode to query measures.

Parameters:

value (str) – Must be one of [“overall”, “components”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_slo_measure¶

class FormulaAndFunctionSLOMeasure(*args, **kwargs)¶

Bases: ModelSimple

SLO measures queries.

Parameters:

value (str) – Must be one of [“good_events”, “bad_events”, “slo_status”, “error_budget_remaining”, “burn_rate”, “error_budget_burndown”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

formula_and_function_slo_query_definition¶

class FormulaAndFunctionSLOQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

A formula and functions metrics query.

Parameters:

additional_query_filters (str, optional) – Additional filters applied to the SLO query.
data_source (FormulaAndFunctionSLODataSource) – Data source for SLO measures queries.
group_mode (FormulaAndFunctionSLOGroupMode, optional) – Group mode to query measures.
measure (FormulaAndFunctionSLOMeasure) – SLO measures queries.
name (str, optional) – Name of the query for use in formulas.
slo_id (str) – ID of an SLO to query measures.
slo_query_type (FormulaAndFunctionSLOQueryType, optional) – Name of the query for use in formulas.

formula_and_function_slo_query_type¶

class FormulaAndFunctionSLOQueryType(*args, **kwargs)¶

Bases: ModelSimple

Name of the query for use in formulas.

Parameters:

value (str) – If omitted defaults to “metric”. Must be one of [“metric”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

free_text_widget_definition¶

class FreeTextWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

Free text is a widget that allows you to add headings to your screenboard. Commonly used to state the overall purpose of the dashboard. Only available on FREE layout dashboards.

Parameters:

color (str, optional) – Color of the text.
font_size (str, optional) – Size of the text.
text (str) – Text to display.
text_align (WidgetTextAlign, optional) – How to align the text on the widget.
type (FreeTextWidgetDefinitionType) – Type of the free text widget.

free_text_widget_definition_type¶

class FreeTextWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the free text widget.

Parameters:

value (str) – If omitted defaults to “free_text”. Must be one of [“free_text”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

funnel_query¶

class FunnelQuery(*args, **kwargs)¶

Bases: ModelNormal

Updated funnel widget.

Parameters:

data_source (FunnelSource) – Source from which to query items to display in the funnel.
query_string (str) – The widget query.
steps ([FunnelStep]) – List of funnel steps.

funnel_request_type¶

class FunnelRequestType(*args, **kwargs)¶

Bases: ModelSimple

Widget request type.

Parameters:

value (str) – If omitted defaults to “funnel”. Must be one of [“funnel”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

funnel_source¶

class FunnelSource(*args, **kwargs)¶

Bases: ModelSimple

Source from which to query items to display in the funnel.

Parameters:

value (str) – If omitted defaults to “rum”. Must be one of [“rum”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

funnel_step¶

class FunnelStep(*args, **kwargs)¶

Bases: ModelNormal

The funnel step.

Parameters:

facet (str) – The facet of the step.
value (str) – The value of the step.

funnel_widget_definition¶

class FunnelWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The funnel visualization displays a funnel of user sessions that maps a sequence of view navigation and user interaction in your application.

Parameters:

requests ([FunnelWidgetRequest]) – Request payload used to query items.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – The title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – The size of the title.
type (FunnelWidgetDefinitionType) – Type of funnel widget.

funnel_widget_definition_type¶

class FunnelWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of funnel widget.

Parameters:

value (str) – If omitted defaults to “funnel”. Must be one of [“funnel”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

funnel_widget_request¶

class FunnelWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated funnel widget.

Parameters:

query (FunnelQuery) – Updated funnel widget.
request_type (FunnelRequestType) – Widget request type.

gcp_account¶

class GCPAccount(*args, **kwargs)¶

Bases: ModelNormal

Your Google Cloud Platform Account.

Parameters:

auth_provider_x509_cert_url (str, optional) – Should be https://www.googleapis.com/oauth2/v1/certs.
auth_uri (str, optional) – Should be https://accounts.google.com/o/oauth2/auth.
automute (bool, optional) – Silence monitors for expected GCE instance shutdowns.
client_email (str, optional) – Your email found in your JSON service account key.
client_id (str, optional) – Your ID found in your JSON service account key.
client_x509_cert_url (str, optional) – Should be https://www.googleapis.com/robot/v1/metadata/x509/$CLIENT_EMAIL where $CLIENT_EMAIL is the email found in your JSON service account key.
errors ([str], optional) – An array of errors.
host_filters (str, optional) – Limit the GCE instances that are pulled into Datadog by using tags. Only hosts that match one of the defined tags are imported into Datadog.
is_cspm_enabled (bool, optional) – When enabled, Datadog will activate the Cloud Security Monitoring product for this service account. Note: This requires resource_collection_enabled to be set to true.
is_security_command_center_enabled (bool, optional) – When enabled, Datadog will attempt to collect Security Command Center Findings. Note: This requires additional permissions on the service account.
private_key (str, optional) – Your private key name found in your JSON service account key.
private_key_id (str, optional) – Your private key ID found in your JSON service account key.
project_id (str, optional) – Your Google Cloud project ID found in your JSON service account key.
resource_collection_enabled (bool, optional) – When enabled, Datadog scans for all resources in your GCP environment.
token_uri (str, optional) – Should be https://accounts.google.com/o/oauth2/token.
type (str, optional) – The value for service_account found in your JSON service account key.

gcp_account_list_response¶

class GCPAccountListResponse(*args, **kwargs)¶

Bases: ModelSimple

Array of GCP account responses.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

geomap_widget_definition¶

class GeomapWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

This visualization displays a series of values by country on a world map.

Parameters:

custom_links ([WidgetCustomLink], optional) – A list of custom links.
requests ([GeomapWidgetRequest]) –
Array of one request object to display in the widget. The request must contain a group-by tag whose value is a country ISO code.

See the Request JSON schema documentation for information about building the REQUEST_SCHEMA.
style (GeomapWidgetDefinitionStyle) – The style to apply to the widget.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – The title of your widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – The size of the title.
type (GeomapWidgetDefinitionType) – Type of the geomap widget.
view (GeomapWidgetDefinitionView) – The view of the world that the map should render.

geomap_widget_definition_style¶

class GeomapWidgetDefinitionStyle(*args, **kwargs)¶

Bases: ModelNormal

The style to apply to the widget.

Parameters:

palette (str) – The color palette to apply to the widget.
palette_flip (bool) – Whether to flip the palette tones.

geomap_widget_definition_type¶

class GeomapWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the geomap widget.

Parameters:

value (str) – If omitted defaults to “geomap”. Must be one of [“geomap”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

geomap_widget_definition_view¶

class GeomapWidgetDefinitionView(*args, **kwargs)¶

Bases: ModelNormal

The view of the world that the map should render.

Parameters:: focus (str) – The 2-letter ISO code of a country to focus the map on. Or WORLD.

geomap_widget_request¶

class GeomapWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

An updated geomap widget.

Parameters:

columns ([ListStreamColumn], optional) – Widget columns.
formulas ([WidgetFormula], optional) – List of formulas that operate on queries.
log_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – The widget metrics query.
queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.
query (ListStreamQuery, optional) – Updated list stream widget.
response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.

graph_snapshot¶

class GraphSnapshot(*args, **kwargs)¶

Bases: ModelNormal

Object representing a graph snapshot.

Parameters:

graph_def (str, optional) – A JSON document defining the graph. graph_def can be used instead of metric_query. The JSON document uses the grammar defined here and should be formatted to a single line then URL encoded.
metric_query (str, optional) – The metric query. One of metric_query or graph_def is required.
snapshot_url (str, optional) – URL of your graph snapshot.

group_widget_definition¶

class GroupWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The groups widget allows you to keep similar graphs together on your timeboard. Each group has a custom header, can hold one to many graphs, and is collapsible.

Parameters:

background_color (str, optional) – Background color of the group title.
banner_img (str, optional) – URL of image to display as a banner for the group.
layout_type (WidgetLayoutType) – Layout type of the group.
show_title (bool, optional) – Whether to show the title or not.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
type (GroupWidgetDefinitionType) – Type of the group widget.
widgets ([Widget]) – List of widget groups.

group_widget_definition_type¶

class GroupWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the group widget.

Parameters:

value (str) – If omitted defaults to “group”. Must be one of [“group”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

heat_map_widget_definition¶

class HeatMapWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The heat map visualization shows metrics aggregated across many tags, such as hosts. The more hosts that have a particular value, the darker that square is.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
events ([WidgetEvent], optional) – List of widget events.
legend_size (str, optional) – Available legend sizes for a widget. Should be one of “0”, “2”, “4”, “8”, “16”, or “auto”.
requests ([HeatMapWidgetRequest]) – List of widget types.
show_legend (bool, optional) – Whether or not to display the legend on this widget.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (HeatMapWidgetDefinitionType) – Type of the heat map widget.
yaxis (WidgetAxis, optional) – Axis controls for the widget.

heat_map_widget_definition_type¶

class HeatMapWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the heat map widget.

Parameters:

value (str) – If omitted defaults to “heatmap”. Must be one of [“heatmap”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

heat_map_widget_request¶

class HeatMapWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated heat map widget.

Parameters:

apm_query (LogQueryDefinition, optional) – The log query.
event_query (EventQueryDefinition, optional) – The event query.
formulas ([WidgetFormula], optional) – List of formulas that operate on queries.
log_query (LogQueryDefinition, optional) – The log query.
network_query (LogQueryDefinition, optional) – The log query.
process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.
profile_metrics_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – Widget query.
queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.
response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.
style (WidgetStyle, optional) – Widget style definition.

host¶

class Host(*args, **kwargs)¶

Bases: ModelNormal

Object representing a host.

Parameters:

aliases ([str], optional) – Host aliases collected by Datadog.
apps ([str], optional) – The Datadog integrations reporting metrics for the host.
aws_name (str, optional) – AWS name of your host.
host_name (str, optional) – The host name.
id (int, optional) – The host ID.
is_muted (bool, optional) – If a host is muted or unmuted.
last_reported_time (int, optional) – Last time the host reported a metric data point.
meta (HostMeta, optional) – Metadata associated with your host.
metrics (HostMetrics, optional) – Host Metrics collected.
mute_timeout (int, none_type, optional) – Timeout of the mute applied to your host.
name (str, optional) – The host name.
sources ([str], optional) – Source or cloud provider associated with your host.
tags_by_source ({str: ([str],)}, optional) – List of tags for each source (AWS, Datadog Agent, Chef..).
up (bool, optional) – Displays UP when the expected metrics are received and displays ??? if no metrics are received.

host_list_response¶

class HostListResponse(*args, **kwargs)¶

Bases: ModelNormal

Response with Host information from Datadog.

Parameters:

host_list ([Host], optional) – Array of hosts.
total_matching (int, optional) – Number of host matching the query.
total_returned (int, optional) – Number of host returned.

host_map_request¶

class HostMapRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated host map.

Parameters:

apm_query (LogQueryDefinition, optional) – The log query.
event_query (LogQueryDefinition, optional) – The log query.
log_query (LogQueryDefinition, optional) – The log query.
network_query (LogQueryDefinition, optional) – The log query.
process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.
profile_metrics_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – Query definition.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.

host_map_widget_definition¶

class HostMapWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The host map widget graphs any metric across your hosts using the same visualization available from the main Host Map page.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
group ([str], optional) – List of tag prefixes to group by.
no_group_hosts (bool, optional) – Whether to show the hosts that don’t fit in a group.
no_metric_hosts (bool, optional) – Whether to show the hosts with no metrics.
node_type (WidgetNodeType, optional) – Which type of node to use in the map.
notes (str, optional) – Notes on the title.
requests (HostMapWidgetDefinitionRequests) – List of definitions.
scope ([str], optional) – List of tags used to filter the map.
style (HostMapWidgetDefinitionStyle, optional) – The style to apply to the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (HostMapWidgetDefinitionType) – Type of the host map widget.

host_map_widget_definition_requests¶

class HostMapWidgetDefinitionRequests(*args, **kwargs)¶

Bases: ModelNormal

List of definitions.

Parameters:

fill (HostMapRequest, optional) – Updated host map.
size (HostMapRequest, optional) – Updated host map.

host_map_widget_definition_style¶

class HostMapWidgetDefinitionStyle(*args, **kwargs)¶

Bases: ModelNormal

The style to apply to the widget.

Parameters:

fill_max (str, optional) – Max value to use to color the map.
fill_min (str, optional) – Min value to use to color the map.
palette (str, optional) – Color palette to apply to the widget.
palette_flip (bool, optional) – Whether to flip the palette tones.

host_map_widget_definition_type¶

class HostMapWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the host map widget.

Parameters:

value (str) – If omitted defaults to “hostmap”. Must be one of [“hostmap”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

host_meta¶

class HostMeta(*args, **kwargs)¶

Bases: ModelNormal

Metadata associated with your host.

Parameters:

agent_checks ([AgentCheck], optional) – A list of Agent checks running on the host.
agent_version (str, optional) – The Datadog Agent version.
cpu_cores (int, optional) – The number of cores.
fbsd_v ([bool, date, datetime, dict, float, int, list, str, UUID, none_type], optional) – An array of Mac versions.
gohai (str, optional) – JSON string containing system information.
install_method (HostMetaInstallMethod, optional) – Agent install method.
mac_v ([bool, date, datetime, dict, float, int, list, str, UUID, none_type], optional) – An array of Mac versions.
machine (str, optional) – The machine architecture.
nix_v ([bool, date, datetime, dict, float, int, list, str, UUID, none_type], optional) – Array of Unix versions.
platform (str, optional) – The OS platform.
processor (str, optional) – The processor.
python_v (str, optional) – The Python version.
socket_fqdn (str, optional) – The socket fqdn.
socket_hostname (str, optional) – The socket hostname.
win_v ([bool, date, datetime, dict, float, int, list, str, UUID, none_type], optional) – An array of Windows versions.

host_meta_install_method¶

class HostMetaInstallMethod(*args, **kwargs)¶

Bases: ModelNormal

Agent install method.

Parameters:

installer_version (str, optional) – The installer version.
tool (str, optional) – Tool used to install the agent.
tool_version (str, optional) – The tool version.

host_metrics¶

class HostMetrics(*args, **kwargs)¶

Bases: ModelNormal

Host Metrics collected.

Parameters:

cpu (float, optional) – The percent of CPU used (everything but idle).
iowait (float, optional) – The percent of CPU spent waiting on the IO (not reported for all platforms).
load (float, optional) – The system load over the last 15 minutes.

host_mute_response¶

class HostMuteResponse(*args, **kwargs)¶

Bases: ModelNormal

Response with the list of muted host for your organization.

Parameters:

action (str, optional) – Action applied to the hosts.
end (int, optional) – POSIX timestamp in seconds when the host is unmuted.
hostname (str, optional) – The host name.
message (str, optional) – Message associated with the mute.

host_mute_settings¶

class HostMuteSettings(*args, **kwargs)¶

Bases: ModelNormal

Combination of settings to mute a host.

Parameters:

end (int, optional) – POSIX timestamp in seconds when the host is unmuted. If omitted, the host remains muted until explicitly unmuted.
message (str, optional) – Message to associate with the muting of this host.
override (bool, optional) – If true and the host is already muted, replaces existing host mute settings.

host_tags¶

class HostTags(*args, **kwargs)¶

Bases: ModelNormal

Set of tags to associate with your host.

Parameters:

host (str, optional) – Your host name.
tags ([str], optional) – A list of tags to apply to the host.

host_totals¶

class HostTotals(*args, **kwargs)¶

Bases: ModelNormal

Total number of host currently monitored by Datadog.

Parameters:

total_active (int, optional) – Total number of active host (UP and ???) reporting to Datadog.
total_up (int, optional) – Number of host that are UP and reporting to Datadog.

hourly_usage_attribution_body¶

class HourlyUsageAttributionBody(*args, **kwargs)¶

Bases: ModelNormal

The usage for one set of tags for one hour.

Parameters:

hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The name of the organization.
public_id (str, optional) – The organization public ID.
region (str, optional) – The region of the Datadog instance that the organization belongs to.
tag_config_source (str, optional) – The source of the usage attribution tag configuration and the selected tags in the format of <source_org_name>:::<selected tag 1>///<selected tag 2>///<selected tag 3>.
tags (UsageAttributionTagNames, none_type, optional) –
Tag keys and values.

A null value here means that the requested tag breakdown cannot be applied because it does not match the tags configured for usage attribution. In this scenario the API returns the total usage, not broken down by tags.
total_usage_sum (float, optional) – Total product usage for the given tags within the hour.
updated_at (str, optional) – Shows the most recent hour in the current month for all organizations where usages are calculated.
usage_type (HourlyUsageAttributionUsageType, optional) – Supported products for hourly usage attribution requests.

hourly_usage_attribution_metadata¶

class HourlyUsageAttributionMetadata(*args, **kwargs)¶

Bases: ModelNormal

The object containing document metadata.

Parameters:: pagination (HourlyUsageAttributionPagination, optional) – The metadata for the current pagination.

hourly_usage_attribution_pagination¶

class HourlyUsageAttributionPagination(*args, **kwargs)¶

Bases: ModelNormal

The metadata for the current pagination.

Parameters:: next_record_id (str, none_type, optional) – The cursor to get the next results (if any). To make the next request, use the same parameters and add next_record_id.

hourly_usage_attribution_response¶

class HourlyUsageAttributionResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the hourly usage attribution by tag(s).

Parameters:

metadata (HourlyUsageAttributionMetadata, optional) – The object containing document metadata.
usage ([HourlyUsageAttributionBody], optional) – Get the hourly usage attribution by tag(s).

hourly_usage_attribution_usage_type¶

class HourlyUsageAttributionUsageType(*args, **kwargs)¶

Bases: ModelSimple

Supported products for hourly usage attribution requests.

Parameters:

value (str) – Must be one of [“api_usage”, “apm_fargate_usage”, “apm_host_usage”, “apm_usm_usage”, “appsec_fargate_usage”, “appsec_usage”, “browser_usage”, “ci_pipeline_indexed_spans_usage”, “ci_test_indexed_spans_usage”, “ci_visibility_itr_usage”, “cloud_siem_usage”, “container_excl_agent_usage”, “container_usage”, “cspm_containers_usage”, “cspm_hosts_usage”, “custom_event_usage”, “custom_ingested_timeseries_usage”, “custom_timeseries_usage”, “cws_containers_usage”, “cws_hosts_usage”, “dbm_hosts_usage”, “dbm_queries_usage”, “estimated_indexed_logs_usage”, “estimated_indexed_spans_usage”, “estimated_ingested_logs_usage”, “estimated_ingested_spans_usage”, “estimated_rum_sessions_usage”, “fargate_usage”, “functions_usage”, “indexed_spans_usage”, “infra_host_usage”, “ingested_logs_bytes_usage”, “ingested_spans_bytes_usage”, “invocations_usage”, “lambda_traced_invocations_usage”, “logs_indexed_15day_usage”, “logs_indexed_180day_usage”, “logs_indexed_30day_usage”, “logs_indexed_360day_usage”, “logs_indexed_3day_usage”, “logs_indexed_45day_usage”, “logs_indexed_60day_usage”, “logs_indexed_7day_usage”, “logs_indexed_90day_usage”, “logs_indexed_custom_retention_usage”, “mobile_app_testing_usage”, “ndm_netflow_usage”, “npm_host_usage”, “obs_pipeline_bytes_usage”, “profiled_container_usage”, “profiled_fargate_usage”, “profiled_host_usage”, “rum_browser_mobile_sessions_usage”, “rum_replay_sessions_usage”, “sds_scanned_bytes_usage”, “serverless_apps_usage”, “siem_ingested_bytes_usage”, “snmp_usage”, “universal_service_monitoring_usage”, “vuln_management_hosts_usage”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

http_log¶

class HTTPLog(*args, **kwargs)¶

Bases: ModelSimple

Structured log message.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

http_log_error¶

class HTTPLogError(*args, **kwargs)¶

Bases: ModelNormal

Invalid query performed.

Parameters:

code (int) – Error code.
message (str) – Error message.

http_log_item¶

class HTTPLogItem(*args, **kwargs)¶

Bases: ModelNormal

Logs that are sent over HTTP.

Parameters:

ddsource (str, optional) – The integration name associated with your log: the technology from which the log originated. When it matches an integration name, Datadog automatically installs the corresponding parsers and facets. See reserved attributes.
ddtags (str, optional) – Tags associated with your logs.
hostname (str, optional) – The name of the originating host of the log.
message (str) – The message reserved attribute of your log. By default, Datadog ingests the value of the message attribute as the body of the log entry. That value is then highlighted and displayed in the Logstream, where it is indexed for full text search.
service (str, optional) –
The name of the application or service generating the log events. It is used to switch from Logs to APM, so make sure you define the same value when you use both products. See reserved attributes.

i_frame_widget_definition¶

class IFrameWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The iframe widget allows you to embed a portion of any other web page on your dashboard. Only available on FREE layout dashboards.

Parameters:

type (IFrameWidgetDefinitionType) – Type of the iframe widget.
url (str) – URL of the iframe.

i_frame_widget_definition_type¶

class IFrameWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the iframe widget.

Parameters:

value (str) – If omitted defaults to “iframe”. Must be one of [“iframe”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

idp_form_data¶

class IdpFormData(*args, **kwargs)¶

Bases: ModelNormal

Object describing the IdP configuration.

Parameters:: idp_file (file_type) – The path to the XML metadata file you wish to upload.

idp_response¶

class IdpResponse(*args, **kwargs)¶

Bases: ModelNormal

The IdP response object.

Parameters:: message (str) – Identity provider response.

image_widget_definition¶

class ImageWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The image widget allows you to embed an image on your dashboard. An image can be a PNG, JPG, or animated GIF. Only available on FREE layout dashboards.

Parameters:

has_background (bool, optional) – Whether to display a background or not.
has_border (bool, optional) – Whether to display a border or not.
horizontal_align (WidgetHorizontalAlign, optional) – Horizontal alignment.
margin (WidgetMargin, optional) – Size of the margins around the image. Note : small and large values are deprecated.
sizing (WidgetImageSizing, optional) – How to size the image on the widget. The values are based on the image object-fit CSS properties. Note : zoom , fit and center values are deprecated.
type (ImageWidgetDefinitionType) – Type of the image widget.
url (str) – URL of the image.
url_dark_theme (str, optional) – URL of the image in dark mode.
vertical_align (WidgetVerticalAlign, optional) – Vertical alignment.

image_widget_definition_type¶

class ImageWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the image widget.

Parameters:

value (str) – If omitted defaults to “image”. Must be one of [“image”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

intake_payload_accepted¶

class IntakePayloadAccepted(*args, **kwargs)¶

Bases: ModelNormal

The payload accepted for intake.

Parameters:: status (str, optional) – The status of the intake payload.

ip_prefixes_agents¶

class IPPrefixesAgents(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for the Agent endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

ip_prefixes_api¶

class IPPrefixesAPI(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for the API endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

ip_prefixes_apm¶

class IPPrefixesAPM(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for the APM endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

ip_prefixes_global¶

class IPPrefixesGlobal(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for all Datadog endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

ip_prefixes_logs¶

class IPPrefixesLogs(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for the Logs endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

ip_prefixes_orchestrator¶

class IPPrefixesOrchestrator(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for the Orchestrator endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

ip_prefixes_process¶

class IPPrefixesProcess(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for the Process endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

ip_prefixes_remote_configuration¶

class IPPrefixesRemoteConfiguration(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for the Remote Configuration endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

ip_prefixes_synthetics¶

class IPPrefixesSynthetics(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for the Synthetics endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv4_by_location ({str: ([str],)}, optional) – List of IPv4 prefixes by location.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.
prefixes_ipv6_by_location ({str: ([str],)}, optional) – List of IPv6 prefixes by location.

ip_prefixes_synthetics_private_locations¶

class IPPrefixesSyntheticsPrivateLocations(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for the Synthetics Private Locations endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

ip_prefixes_webhooks¶

class IPPrefixesWebhooks(*args, **kwargs)¶

Bases: ModelNormal

Available prefix information for the Webhook endpoints.

Parameters:

prefixes_ipv4 ([str], optional) – List of IPv4 prefixes.
prefixes_ipv6 ([str], optional) – List of IPv6 prefixes.

ip_ranges¶

class IPRanges(*args, **kwargs)¶

Bases: ModelNormal

IP ranges.

Parameters:

agents (IPPrefixesAgents, optional) – Available prefix information for the Agent endpoints.
api (IPPrefixesAPI, optional) – Available prefix information for the API endpoints.
apm (IPPrefixesAPM, optional) – Available prefix information for the APM endpoints.
_global (IPPrefixesGlobal, optional) – Available prefix information for all Datadog endpoints.
logs (IPPrefixesLogs, optional) – Available prefix information for the Logs endpoints.
modified (str, optional) – Date when last updated, in the form YYYY-MM-DD-hh-mm-ss.
orchestrator (IPPrefixesOrchestrator, optional) – Available prefix information for the Orchestrator endpoints.
process (IPPrefixesProcess, optional) – Available prefix information for the Process endpoints.
remote_configuration (IPPrefixesRemoteConfiguration, optional) – Available prefix information for the Remote Configuration endpoints.
synthetics (IPPrefixesSynthetics, optional) – Available prefix information for the Synthetics endpoints.
synthetics_private_locations (IPPrefixesSyntheticsPrivateLocations, optional) – Available prefix information for the Synthetics Private Locations endpoints.
version (int, optional) – Version of the IP list.
webhooks (IPPrefixesWebhooks, optional) – Available prefix information for the Webhook endpoints.

list_stream_column¶

class ListStreamColumn(*args, **kwargs)¶

Bases: ModelNormal

Widget column.

Parameters:

field (str) – Widget column field.
width (ListStreamColumnWidth) – Widget column width.

list_stream_column_width¶

class ListStreamColumnWidth(*args, **kwargs)¶

Bases: ModelSimple

Widget column width.

Parameters:

value (str) – Must be one of [“auto”, “compact”, “full”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

list_stream_compute_aggregation¶

class ListStreamComputeAggregation(*args, **kwargs)¶

Bases: ModelSimple

Aggregation value.

Parameters:

value (str) – Must be one of [“count”, “cardinality”, “median”, “pc75”, “pc90”, “pc95”, “pc98”, “pc99”, “sum”, “min”, “max”, “avg”, “earliest”, “latest”, “most_frequent”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

list_stream_compute_items¶

class ListStreamComputeItems(*args, **kwargs)¶

Bases: ModelNormal

List of facets and aggregations which to compute.

Parameters:

aggregation (ListStreamComputeAggregation) – Aggregation value.
facet (str, optional) – Facet name.

list_stream_group_by_items¶

class ListStreamGroupByItems(*args, **kwargs)¶

Bases: ModelNormal

List of facets on which to group.

Parameters:: facet (str) – Facet name.

list_stream_query¶

class ListStreamQuery(*args, **kwargs)¶

Bases: ModelNormal

Updated list stream widget.

Parameters:

compute ([ListStreamComputeItems], optional) – Compute configuration for the List Stream Widget. Compute can be used only with the logs_transaction_stream (from 1 to 5 items) list stream source.
data_source (ListStreamSource) – Source from which to query items to display in the stream.
event_size (WidgetEventSize, optional) – Size to use to display an event.
group_by ([ListStreamGroupByItems], optional) – Group by configuration for the List Stream Widget. Group by can be used only with logs_pattern_stream (up to 3 items) or logs_transaction_stream (one group by item is required) list stream source.
indexes ([str], optional) – List of indexes.
query_string (str) – Widget query.
sort (WidgetFieldSort, optional) – Which column and order to sort by
storage (str, optional) – Option for storage location. Feature in Private Beta.

list_stream_response_format¶

class ListStreamResponseFormat(*args, **kwargs)¶

Bases: ModelSimple

Widget response format.

Parameters:

value (str) – If omitted defaults to “event_list”. Must be one of [“event_list”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

list_stream_source¶

class ListStreamSource(*args, **kwargs)¶

Bases: ModelSimple

Source from which to query items to display in the stream.

Parameters:

value (str) – If omitted defaults to “apm_issue_stream”. Must be one of [“logs_stream”, “audit_stream”, “ci_pipeline_stream”, “ci_test_stream”, “rum_issue_stream”, “apm_issue_stream”, “trace_stream”, “logs_issue_stream”, “logs_pattern_stream”, “logs_transaction_stream”, “event_stream”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

list_stream_widget_definition¶

class ListStreamWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The list stream visualization displays a table of recent events in your application that match a search criteria using user-defined columns.

Parameters:

legend_size (str, optional) – Available legend sizes for a widget. Should be one of “0”, “2”, “4”, “8”, “16”, or “auto”.
requests ([ListStreamWidgetRequest]) – Request payload used to query items.
show_legend (bool, optional) – Whether or not to display the legend on this widget.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (ListStreamWidgetDefinitionType) – Type of the list stream widget.

list_stream_widget_definition_type¶

class ListStreamWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the list stream widget.

Parameters:

value (str) – If omitted defaults to “list_stream”. Must be one of [“list_stream”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

list_stream_widget_request¶

class ListStreamWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated list stream widget.

Parameters:

columns ([ListStreamColumn]) – Widget columns.
query (ListStreamQuery) – Updated list stream widget.
response_format (ListStreamResponseFormat) – Widget response format.

log¶

class Log(*args, **kwargs)¶

Bases: ModelNormal

Object describing a log after being processed and stored by Datadog.

Parameters:

content (LogContent, optional) – JSON object containing all log attributes and their associated values.
id (str, optional) – ID of the Log.

log_content¶

class LogContent(*args, **kwargs)¶

Bases: ModelNormal

JSON object containing all log attributes and their associated values.

Parameters:

attributes ({str: (bool, date, datetime, dict, float, int, list, str, UUID, none_type,)}, optional) – JSON object of attributes from your log.
host (str, optional) – Name of the machine from where the logs are being sent.
message (str, optional) –
The message reserved attribute of your log. By default, Datadog ingests the value of the message attribute as the body of the log entry. That value is then highlighted and displayed in the Logstream, where it is indexed for full text search.
service (str, optional) – The name of the application or service generating the log events. It is used to switch from Logs to APM, so make sure you define the same value when you use both products.
tags ([str], optional) – Array of tags associated with your log.
timestamp (datetime, optional) – Timestamp of your log.

log_query_definition¶

class LogQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

The log query.

Parameters:

compute (LogsQueryCompute, optional) – Define computation for a log query.
group_by ([LogQueryDefinitionGroupBy], optional) – List of tag prefixes to group by in the case of a cluster check.
index (str, optional) – A coma separated-list of index names. Use “*” query all indexes at once. Multiple Indexes
multi_compute ([LogsQueryCompute], optional) – This field is mutually exclusive with compute.
search (LogQueryDefinitionSearch, optional) – The query being made on the logs.

log_query_definition_group_by¶

class LogQueryDefinitionGroupBy(*args, **kwargs)¶

Bases: ModelNormal

Defined items in the group.

Parameters:

facet (str) – Facet name.
limit (int, optional) – Maximum number of items in the group.
sort (LogQueryDefinitionGroupBySort, optional) – Define a sorting method.

log_query_definition_group_by_sort¶

class LogQueryDefinitionGroupBySort(*args, **kwargs)¶

Bases: ModelNormal

Define a sorting method.

Parameters:

aggregation (str) – The aggregation method.
facet (str, optional) – Facet name.
order (WidgetSort) – Widget sorting methods.

log_query_definition_search¶

class LogQueryDefinitionSearch(*args, **kwargs)¶

Bases: ModelNormal

The query being made on the logs.

Parameters:: query (str) – Search value to apply.

log_stream_widget_definition¶

class LogStreamWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The Log Stream displays a log flow matching the defined query. Only available on FREE layout dashboards.

Parameters:

columns ([str], optional) – Which columns to display on the widget.
indexes ([str], optional) – An array of index names to query in the stream. Use [] to query all indexes at once.
logset (str, optional) – ID of the log set to use. Deprecated.
message_display (WidgetMessageDisplay, optional) – Amount of log lines to display
query (str, optional) – Query to filter the log stream with.
show_date_column (bool, optional) – Whether to show the date column or not
show_message_column (bool, optional) – Whether to show the message column or not
sort (WidgetFieldSort, optional) – Which column and order to sort by
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (LogStreamWidgetDefinitionType) – Type of the log stream widget.

log_stream_widget_definition_type¶

class LogStreamWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the log stream widget.

Parameters:

value (str) – If omitted defaults to “log_stream”. Must be one of [“log_stream”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_api_error¶

class LogsAPIError(*args, **kwargs)¶

Bases: ModelNormal

Error returned by the Logs API

Parameters:

code (str, optional) – Code identifying the error
details ([LogsAPIError], optional) – Additional error details
message (str, optional) – Error message

logs_api_error_response¶

class LogsAPIErrorResponse(*args, **kwargs)¶

Bases: ModelNormal

Response returned by the Logs API when errors occur.

Parameters:: error (LogsAPIError, optional) – Error returned by the Logs API

logs_arithmetic_processor¶

class LogsArithmeticProcessor(*args, **kwargs)¶

Bases: ModelNormal

Use the Arithmetic Processor to add a new attribute (without spaces or special characters in the new attribute name) to a log with the result of the provided formula. This enables you to remap different time attributes with different units into a single attribute, or to compute operations on attributes within the same log.

The formula can use parentheses and the basic arithmetic operators - , + , * , /.

By default, the calculation is skipped if an attribute is missing. Select “Replace missing attribute by 0” to automatically populate missing attribute values with 0 to ensure that the calculation is done. An attribute is missing if it is not found in the log attributes, or if it cannot be converted to a number.

Notes :

The operator - needs to be space split in the formula as it can also be contained in attribute names.
If the target attribute already exists, it is overwritten by the result of the formula.
Results are rounded up to the 9th decimal. For example, if the result of the formula is 0.1234567891 , the actual value stored for the attribute is 0.123456789.
If you need to scale a unit of measure, see Scale Filter.

Parameters:

expression (str) – Arithmetic operation between one or more log attributes.
is_enabled (bool, optional) – Whether or not the processor is enabled.
is_replace_missing (bool, optional) – If true , it replaces all missing attributes of expression by 0 , false skip the operation if an attribute is missing.
name (str, optional) – Name of the processor.
target (str) – Name of the attribute that contains the result of the arithmetic operation.
type (LogsArithmeticProcessorType) – Type of logs arithmetic processor.

logs_arithmetic_processor_type¶

class LogsArithmeticProcessorType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs arithmetic processor.

Parameters:

value (str) – If omitted defaults to “arithmetic-processor”. Must be one of [“arithmetic-processor”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_attribute_remapper¶

class LogsAttributeRemapper(*args, **kwargs)¶

Bases: ModelNormal

The remapper processor remaps any source attribute(s) or tag to another target attribute or tag. Constraints on the tag/attribute name are explained in the Tag Best Practice documentation. Some additional constraints are applied as : or , are not allowed in the target tag/attribute name.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
override_on_conflict (bool, optional) – Override or not the target element if already set,
preserve_source (bool, optional) – Remove or preserve the remapped source element.
source_type (str, optional) – Defines if the sources are from log attribute or tag.
sources ([str]) – Array of source attributes.
target (str) – Final attribute or tag name to remap the sources to.
target_format (TargetFormatType, optional) – If the target_type of the remapper is attribute , try to cast the value to a new specific type. If the cast is not possible, the original type is kept. string , integer , or double are the possible types. If the target_type is tag , this parameter may not be specified.
target_type (str, optional) – Defines if the final attribute or tag name is from log attribute or tag.
type (LogsAttributeRemapperType) – Type of logs attribute remapper.

logs_attribute_remapper_type¶

class LogsAttributeRemapperType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs attribute remapper.

Parameters:

value (str) – If omitted defaults to “attribute-remapper”. Must be one of [“attribute-remapper”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_by_retention¶

class LogsByRetention(*args, **kwargs)¶

Bases: ModelNormal

Object containing logs usage data broken down by retention period.

Parameters:

orgs (LogsByRetentionOrgs, optional) – Indexed logs usage summary for each organization for each retention period with usage.
usage ([LogsRetentionAggSumUsage], optional) – Aggregated index logs usage for each retention period with usage.
usage_by_month (LogsByRetentionMonthlyUsage, optional) – Object containing a summary of indexed logs usage by retention period for a single month.

logs_by_retention_monthly_usage¶

class LogsByRetentionMonthlyUsage(*args, **kwargs)¶

Bases: ModelNormal

Object containing a summary of indexed logs usage by retention period for a single month.

Parameters:

date (datetime, optional) – The month for the usage.
usage ([LogsRetentionSumUsage], optional) – Indexed logs usage for each active retention for the month.

logs_by_retention_org_usage¶

class LogsByRetentionOrgUsage(*args, **kwargs)¶

Bases: ModelNormal

Indexed logs usage by retention for a single organization.

Parameters:: usage ([LogsRetentionSumUsage], optional) – Indexed logs usage for each active retention for the organization.

logs_by_retention_orgs¶

class LogsByRetentionOrgs(*args, **kwargs)¶

Bases: ModelNormal

Indexed logs usage summary for each organization for each retention period with usage.

Parameters:: usage ([LogsByRetentionOrgUsage], optional) – Indexed logs usage summary for each organization.

logs_category_processor¶

class LogsCategoryProcessor(*args, **kwargs)¶

Bases: ModelNormal

Use the Category Processor to add a new attribute (without spaces or special characters in the new attribute name) to a log matching a provided search query. Use categories to create groups for an analytical view. For example, URL groups, machine groups, environments, and response time buckets.

Notes :

The syntax of the query is the one of Logs Explorer search bar. The query can be done on any log attribute or tag, whether it is a facet or not. Wildcards can also be used inside your query.
Once the log has matched one of the Processor queries, it stops. Make sure they are properly ordered in case a log could match several queries.
The names of the categories must be unique.
Once defined in the Category Processor, you can map categories to log status using the Log Status Remapper.

Parameters:

categories ([LogsCategoryProcessorCategory]) – Array of filters to match or not a log and their corresponding name to assign a custom value to the log.
is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
target (str) – Name of the target attribute which value is defined by the matching category.
type (LogsCategoryProcessorType) – Type of logs category processor.

logs_category_processor_category¶

class LogsCategoryProcessorCategory(*args, **kwargs)¶

Bases: ModelNormal

Object describing the logs filter.

Parameters:

filter (LogsFilter, optional) – Filter for logs.
name (str, optional) – Value to assign to the target attribute.

logs_category_processor_type¶

class LogsCategoryProcessorType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs category processor.

Parameters:

value (str) – If omitted defaults to “category-processor”. Must be one of [“category-processor”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_daily_limit_reset¶

class LogsDailyLimitReset(*args, **kwargs)¶

Bases: ModelNormal

Object containing options to override the default daily limit reset time.

Parameters:

reset_time (str, optional) – String in HH:00 format representing the time of day the daily limit should be reset. The hours must be between 00 and 23 (inclusive).
reset_utc_offset (str, optional) – String in (-|+)HH:00 format representing the UTC offset to apply to the given reset time. The hours must be between -12 and +14 (inclusive).

logs_date_remapper¶

class LogsDateRemapper(*args, **kwargs)¶

Bases: ModelNormal

As Datadog receives logs, it timestamps them using the value(s) from any of these default attributes.

timestamp
date
_timestamp
Timestamp
eventTime
published_date

If your logs put their dates in an attribute not in this list, use the log date Remapper Processor to define their date attribute as the official log timestamp. The recognized date formats are ISO8601, UNIX (the milliseconds EPOCH format), and RFC3164.

Note: If your logs don’t contain any of the default attributes and you haven’t defined your own date attribute, Datadog timestamps the logs with the date it received them.

If multiple log date remapper processors can be applied to a given log, only the first one (according to the pipelines order) is taken into account.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
sources ([str]) – Array of source attributes.
type (LogsDateRemapperType) – Type of logs date remapper.

logs_date_remapper_type¶

class LogsDateRemapperType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs date remapper.

Parameters:

value (str) – If omitted defaults to “date-remapper”. Must be one of [“date-remapper”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_exclusion¶

class LogsExclusion(*args, **kwargs)¶

Bases: ModelNormal

Represents the index exclusion filter object from configuration API.

Parameters:

filter (LogsExclusionFilter, optional) – Exclusion filter is defined by a query, a sampling rule, and a active/inactive toggle.
is_enabled (bool, optional) – Whether or not the exclusion filter is active.
name (str) – Name of the index exclusion filter.

logs_exclusion_filter¶

class LogsExclusionFilter(*args, **kwargs)¶

Bases: ModelNormal

Exclusion filter is defined by a query, a sampling rule, and a active/inactive toggle.

Parameters:

query (str, optional) – Default query is * , meaning all logs flowing in the index would be excluded. Scope down exclusion filter to only a subset of logs with a log query.
sample_rate (float) – Sample rate to apply to logs going through this exclusion filter, a value of 1.0 excludes all logs matching the query.

logs_filter¶

class LogsFilter(*args, **kwargs)¶

Bases: ModelNormal

Filter for logs.

Parameters:: query (str, optional) – The filter query.

logs_geo_ip_parser¶

class LogsGeoIPParser(*args, **kwargs)¶

Bases: ModelNormal

The GeoIP parser takes an IP address attribute and extracts if available the Continent, Country, Subdivision, and City information in the target attribute path.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
sources ([str]) – Array of source attributes.
target (str) – Name of the parent attribute that contains all the extracted details from the sources.
type (LogsGeoIPParserType) – Type of GeoIP parser.

logs_geo_ip_parser_type¶

class LogsGeoIPParserType(*args, **kwargs)¶

Bases: ModelSimple

Type of GeoIP parser.

Parameters:

value (str) – If omitted defaults to “geo-ip-parser”. Must be one of [“geo-ip-parser”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_grok_parser¶

class LogsGrokParser(*args, **kwargs)¶

Bases: ModelNormal

Create custom grok rules to parse the full message or a specific attribute of your raw event. For more information, see the parsing section.

Parameters:

grok (LogsGrokParserRules) – Set of rules for the grok parser.
is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
samples ([str], optional) – List of sample logs to test this grok parser.
source (str) – Name of the log attribute to parse.
type (LogsGrokParserType) – Type of logs grok parser.

logs_grok_parser_rules¶

class LogsGrokParserRules(*args, **kwargs)¶

Bases: ModelNormal

Set of rules for the grok parser.

Parameters:

match_rules (str) – List of match rules for the grok parser, separated by a new line.
support_rules (str, optional) – List of support rules for the grok parser, separated by a new line.

logs_grok_parser_type¶

class LogsGrokParserType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs grok parser.

Parameters:

value (str) – If omitted defaults to “grok-parser”. Must be one of [“grok-parser”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_index¶

class LogsIndex(*args, **kwargs)¶

Bases: ModelNormal

Object describing a Datadog Log index.

Parameters:

daily_limit (int, optional) – The number of log events you can send in this index per day before you are rate-limited.
daily_limit_reset (LogsDailyLimitReset, optional) – Object containing options to override the default daily limit reset time.
daily_limit_warning_threshold_percentage (float, optional) – A percentage threshold of the daily quota at which a Datadog warning event is generated.
exclusion_filters ([LogsExclusion], optional) – An array of exclusion objects. The logs are tested against the query of each filter, following the order of the array. Only the first matching active exclusion matters, others (if any) are ignored.
filter (LogsFilter) – Filter for logs.
is_rate_limited (bool, optional) – A boolean stating if the index is rate limited, meaning more logs than the daily limit have been sent. Rate limit is reset every-day at 2pm UTC.
name (str) – The name of the index.
num_retention_days (int, optional) – The number of days before logs are deleted from this index. Available values depend on retention plans specified in your organization’s contract/subscriptions.

logs_index_list_response¶

class LogsIndexListResponse(*args, **kwargs)¶

Bases: ModelNormal

Object with all Index configurations for a given organization.

Parameters:: indexes ([LogsIndex], optional) – Array of Log index configurations.

logs_index_update_request¶

class LogsIndexUpdateRequest(*args, **kwargs)¶

Bases: ModelNormal

Object for updating a Datadog Log index.

Parameters:

daily_limit (int, optional) – The number of log events you can send in this index per day before you are rate-limited.
daily_limit_reset (LogsDailyLimitReset, optional) – Object containing options to override the default daily limit reset time.
daily_limit_warning_threshold_percentage (float, optional) – A percentage threshold of the daily quota at which a Datadog warning event is generated.
disable_daily_limit (bool, optional) – If true, sets the daily_limit value to null and the index is not limited on a daily basis (any specified daily_limit value in the request is ignored). If false or omitted, the index’s current daily_limit is maintained.
exclusion_filters ([LogsExclusion], optional) – An array of exclusion objects. The logs are tested against the query of each filter, following the order of the array. Only the first matching active exclusion matters, others (if any) are ignored.
filter (LogsFilter) – Filter for logs.
num_retention_days (int, optional) –
The number of days before logs are deleted from this index. Available values depend on retention plans specified in your organization’s contract/subscriptions.

Note: Changing the retention for an index adjusts the length of retention for all logs already in this index. It may also affect billing.

logs_indexes_order¶

class LogsIndexesOrder(*args, **kwargs)¶

Bases: ModelNormal

Object containing the ordered list of log index names.

Parameters:: index_names ([str]) – Array of strings identifying by their name(s) the index(es) of your organization. Logs are tested against the query filter of each index one by one, following the order of the array. Logs are eventually stored in the first matching index.

logs_list_request¶

class LogsListRequest(*args, **kwargs)¶

Bases: ModelNormal

Object to send with the request to retrieve a list of logs from your Organization.

Parameters:

index (str, optional) – The log index on which the request is performed. For multi-index organizations, the default is all live indexes. Historical indexes of rehydrated logs must be specified.
limit (int, optional) – Number of logs return in the response.
query (str, optional) – The search query - following the log search syntax.
sort (LogsSort, optional) – Time-ascending asc or time-descending desc results.
start_at (str, optional) –
Hash identifier of the first log to return in the list, available in a log id attribute. This parameter is used for the pagination feature.

Note : This parameter is ignored if the corresponding log is out of the scope of the specified time window.
time (LogsListRequestTime) – Timeframe to retrieve the log from.

logs_list_request_time¶

class LogsListRequestTime(*args, **kwargs)¶

Bases: ModelNormal

Timeframe to retrieve the log from.

Parameters:

_from (datetime) – Minimum timestamp for requested logs.
timezone (str, optional) – Timezone can be specified both as an offset (for example “UTC+03:00”) or a regional zone (for example “Europe/Paris”).
to (datetime) – Maximum timestamp for requested logs.

logs_list_response¶

class LogsListResponse(*args, **kwargs)¶

Bases: ModelNormal

Response object with all logs matching the request and pagination information.

Parameters:

logs ([Log], optional) – Array of logs matching the request and the nextLogId if sent.
next_log_id (str, none_type, optional) – Hash identifier of the next log to return in the list. This parameter is used for the pagination feature.
status (str, optional) – Status of the response.

logs_lookup_processor¶

class LogsLookupProcessor(*args, **kwargs)¶

Bases: ModelNormal

Use the Lookup Processor to define a mapping between a log attribute and a human readable value saved in the processors mapping table. For example, you can use the Lookup Processor to map an internal service ID into a human readable service name. Alternatively, you could also use it to check if the MAC address that just attempted to connect to the production environment belongs to your list of stolen machines.

Parameters:

default_lookup (str, optional) – Value to set the target attribute if the source value is not found in the list.
is_enabled (bool, optional) – Whether or not the processor is enabled.
lookup_table ([str]) – Mapping table of values for the source attribute and their associated target attribute values, formatted as ["source_key1,target_value1", "source_key2,target_value2"]
name (str, optional) – Name of the processor.
source (str) – Source attribute used to perform the lookup.
target (str) – Name of the attribute that contains the corresponding value in the mapping list or the default_lookup if not found in the mapping list.
type (LogsLookupProcessorType) – Type of logs lookup processor.

logs_lookup_processor_type¶

class LogsLookupProcessorType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs lookup processor.

Parameters:

value (str) – If omitted defaults to “lookup-processor”. Must be one of [“lookup-processor”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_message_remapper¶

class LogsMessageRemapper(*args, **kwargs)¶

Bases: ModelNormal

The message is a key attribute in Datadog. It is displayed in the message column of the Log Explorer and you can do full string search on it. Use this Processor to define one or more attributes as the official log message.

Note: If multiple log message remapper processors can be applied to a given log, only the first one (according to the pipeline order) is taken into account.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
sources ([str]) – Array of source attributes.
type (LogsMessageRemapperType) – Type of logs message remapper.

logs_message_remapper_type¶

class LogsMessageRemapperType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs message remapper.

Parameters:

value (str) – If omitted defaults to “message-remapper”. Must be one of [“message-remapper”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_pipeline¶

class LogsPipeline(*args, **kwargs)¶

Bases: ModelNormal

Pipelines and processors operate on incoming logs, parsing and transforming them into structured attributes for easier querying.

Note : These endpoints are only available for admin users. Make sure to use an application key created by an admin.

Parameters:

filter (LogsFilter, optional) – Filter for logs.
id (str, optional) – ID of the pipeline.
is_enabled (bool, optional) – Whether or not the pipeline is enabled.
is_read_only (bool, optional) – Whether or not the pipeline can be edited.
name (str) – Name of the pipeline.
processors ([LogsProcessor], optional) – Ordered list of processors in this pipeline.
type (str, optional) – Type of pipeline.

logs_pipeline_list¶

class LogsPipelineList(*args, **kwargs)¶

Bases: ModelSimple

Array of pipeline ID strings.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_pipeline_processor¶

class LogsPipelineProcessor(*args, **kwargs)¶

Bases: ModelNormal

Nested Pipelines are pipelines within a pipeline. Use Nested Pipelines to split the processing into two steps. For example, first use a high-level filtering such as team and then a second level of filtering based on the integration, service, or any other tag or attribute.

A pipeline can contain Nested Pipelines and Processors whereas a Nested Pipeline can only contain Processors.

Parameters:

filter (LogsFilter, optional) – Filter for logs.
is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
processors ([LogsProcessor], optional) – Ordered list of processors in this pipeline.
type (LogsPipelineProcessorType) – Type of logs pipeline processor.

logs_pipeline_processor_type¶

class LogsPipelineProcessorType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs pipeline processor.

Parameters:

value (str) – If omitted defaults to “pipeline”. Must be one of [“pipeline”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_pipelines_order¶

class LogsPipelinesOrder(*args, **kwargs)¶

Bases: ModelNormal

Object containing the ordered list of pipeline IDs.

Parameters:: pipeline_ids ([str]) – Ordered Array of <PIPELINE_ID> strings, the order of pipeline IDs in the array define the overall Pipelines order for Datadog.

logs_processor¶

class LogsProcessor(*args, **kwargs)¶

Bases: ModelComposed

Definition of a logs processor.

Parameters:

grok (LogsGrokParserRules) – Set of rules for the grok parser.
is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
samples ([str], optional) – List of sample logs to test this grok parser.
source (str) – Name of the log attribute to parse.
type (LogsGrokParserType) – Type of logs grok parser.
sources ([str]) – Array of source attributes.
override_on_conflict (bool, optional) – Override or not the target element if already set,
preserve_source (bool, optional) – Remove or preserve the remapped source element.
source_type (str, optional) – Defines if the sources are from log attribute or tag.
target (str) – Final attribute or tag name to remap the sources to.
target_format (TargetFormatType, optional) – If the target_type of the remapper is attribute, try to cast the value to a new specific type. If the cast is not possible, the original type is kept. string, integer, or double are the possible types. If the target_type is tag, this parameter may not be specified.
target_type (str, optional) – Defines if the final attribute or tag name is from log attribute or tag.
normalize_ending_slashes (bool, none_type, optional) – Normalize the ending slashes or not.
is_encoded (bool, optional) – Define if the source attribute is URL encoded or not.
categories ([LogsCategoryProcessorCategory]) – Array of filters to match or not a log and their corresponding name to assign a custom value to the log.
expression (str) – Arithmetic operation between one or more log attributes.
is_replace_missing (bool, optional) – If true, it replaces all missing attributes of expression by 0, false skip the operation if an attribute is missing.
template (str) – A formula with one or more attributes and raw text.
filter (LogsFilter, optional) – Filter for logs.
processors ([LogsProcessor], optional) – Ordered list of processors in this pipeline.
default_lookup (str, optional) – Value to set the target attribute if the source value is not found in the list.
lookup_table ([str]) – Mapping table of values for the source attribute and their associated target attribute values, formatted as [“source_key1,target_value1”, “source_key2,target_value2”]
lookup_enrichment_table (str) – Name of the Reference Table for the source attribute and their associated target attribute values.

logs_query_compute¶

class LogsQueryCompute(*args, **kwargs)¶

Bases: ModelNormal

Define computation for a log query.

Parameters:

aggregation (str) – The aggregation method.
facet (str, optional) – Facet name.
interval (int, optional) – Define a time interval in seconds.

logs_retention_agg_sum_usage¶

class LogsRetentionAggSumUsage(*args, **kwargs)¶

Bases: ModelNormal

Object containing indexed logs usage aggregated across organizations and months for a retention period.

Parameters:

logs_indexed_logs_usage_agg_sum (int, optional) – Total indexed logs for this retention period.
logs_live_indexed_logs_usage_agg_sum (int, optional) – Live indexed logs for this retention period.
logs_rehydrated_indexed_logs_usage_agg_sum (int, optional) – Rehydrated indexed logs for this retention period.
retention (str, optional) – The retention period in days or “custom” for all custom retention periods.

logs_retention_sum_usage¶

class LogsRetentionSumUsage(*args, **kwargs)¶

Bases: ModelNormal

Object containing indexed logs usage grouped by retention period and summed.

Parameters:

logs_indexed_logs_usage_sum (int, optional) – Total indexed logs for this retention period.
logs_live_indexed_logs_usage_sum (int, optional) – Live indexed logs for this retention period.
logs_rehydrated_indexed_logs_usage_sum (int, optional) – Rehydrated indexed logs for this retention period.
retention (str, optional) – The retention period in days or “custom” for all custom retention periods.

logs_service_remapper¶

class LogsServiceRemapper(*args, **kwargs)¶

Bases: ModelNormal

Use this processor if you want to assign one or more attributes as the official service.

Note: If multiple service remapper processors can be applied to a given log, only the first one (according to the pipeline order) is taken into account.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
sources ([str]) – Array of source attributes.
type (LogsServiceRemapperType) – Type of logs service remapper.

logs_service_remapper_type¶

class LogsServiceRemapperType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs service remapper.

Parameters:

value (str) – If omitted defaults to “service-remapper”. Must be one of [“service-remapper”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_sort¶

class LogsSort(*args, **kwargs)¶

Bases: ModelSimple

Time-ascending asc or time-descending desc results.

Parameters:

value (str) – Must be one of [“asc”, “desc”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_status_remapper¶

class LogsStatusRemapper(*args, **kwargs)¶

Bases: ModelNormal

Use this Processor if you want to assign some attributes as the official status.

Each incoming status value is mapped as follows.

Integers from 0 to 7 map to the Syslog severity standards
Strings beginning with emerg or f (case-insensitive) map to emerg (0)
Strings beginning with a (case-insensitive) map to alert (1)
Strings beginning with c (case-insensitive) map to critical (2)
Strings beginning with err (case-insensitive) map to error (3)
Strings beginning with w (case-insensitive) map to warning (4)
Strings beginning with n (case-insensitive) map to notice (5)
Strings beginning with i (case-insensitive) map to info (6)
Strings beginning with d , trace or verbose (case-insensitive) map to debug (7)
Strings beginning with o or matching OK or Success (case-insensitive) map to OK
All others map to info (6)

Note: If multiple log status remapper processors can be applied to a given log, only the first one (according to the pipelines order) is taken into account.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
sources ([str]) – Array of source attributes.
type (LogsStatusRemapperType) – Type of logs status remapper.

logs_status_remapper_type¶

class LogsStatusRemapperType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs status remapper.

Parameters:

value (str) – If omitted defaults to “status-remapper”. Must be one of [“status-remapper”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_string_builder_processor¶

class LogsStringBuilderProcessor(*args, **kwargs)¶

Bases: ModelNormal

Use the string builder processor to add a new attribute (without spaces or special characters) to a log with the result of the provided template. This enables aggregation of different attributes or raw strings into a single attribute.

The template is defined by both raw text and blocks with the syntax %{attribute_path}.

Notes :

The processor only accepts attributes with values or an array of values in the blocks.
If an attribute cannot be used (object or array of object), it is replaced by an empty string or the entire operation is skipped depending on your selection.
If the target attribute already exists, it is overwritten by the result of the template.
Results of the template cannot exceed 256 characters.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
is_replace_missing (bool, optional) – If true, it replaces all missing attributes of template by an empty string. If false (default), skips the operation for missing attributes.
name (str, optional) – Name of the processor.
target (str) – The name of the attribute that contains the result of the template.
template (str) – A formula with one or more attributes and raw text.
type (LogsStringBuilderProcessorType) – Type of logs string builder processor.

logs_string_builder_processor_type¶

class LogsStringBuilderProcessorType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs string builder processor.

Parameters:

value (str) – If omitted defaults to “string-builder-processor”. Must be one of [“string-builder-processor”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_trace_remapper¶

class LogsTraceRemapper(*args, **kwargs)¶

Bases: ModelNormal

There are two ways to improve correlation between application traces and logs.

Follow the documentation on how to inject a trace ID in the application logs and by default log integrations take care of all the rest of the setup.
Use the Trace remapper processor to define a log attribute as its associated trace ID.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
sources ([str], optional) – Array of source attributes.
type (LogsTraceRemapperType) – Type of logs trace remapper.

logs_trace_remapper_type¶

class LogsTraceRemapperType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs trace remapper.

Parameters:

value (str) – If omitted defaults to “trace-id-remapper”. Must be one of [“trace-id-remapper”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_url_parser¶

class LogsURLParser(*args, **kwargs)¶

Bases: ModelNormal

This processor extracts query parameters and other important parameters from a URL.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
name (str, optional) – Name of the processor.
normalize_ending_slashes (bool, none_type, optional) – Normalize the ending slashes or not.
sources ([str]) – Array of source attributes.
target (str) – Name of the parent attribute that contains all the extracted details from the sources.
type (LogsURLParserType) – Type of logs URL parser.

logs_url_parser_type¶

class LogsURLParserType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs URL parser.

Parameters:

value (str) – If omitted defaults to “url-parser”. Must be one of [“url-parser”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

logs_user_agent_parser¶

class LogsUserAgentParser(*args, **kwargs)¶

Bases: ModelNormal

The User-Agent parser takes a User-Agent attribute and extracts the OS, browser, device, and other user data. It recognizes major bots like the Google Bot, Yahoo Slurp, and Bing.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
is_encoded (bool, optional) – Define if the source attribute is URL encoded or not.
name (str, optional) – Name of the processor.
sources ([str]) – Array of source attributes.
target (str) – Name of the parent attribute that contains all the extracted details from the sources.
type (LogsUserAgentParserType) – Type of logs User-Agent parser.

logs_user_agent_parser_type¶

class LogsUserAgentParserType(*args, **kwargs)¶

Bases: ModelSimple

Type of logs User-Agent parser.

Parameters:

value (str) – If omitted defaults to “user-agent-parser”. Must be one of [“user-agent-parser”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

matching_downtime¶

class MatchingDowntime(*args, **kwargs)¶

Bases: ModelNormal

Object describing a downtime that matches this monitor.

Parameters:

end (int, none_type, optional) – POSIX timestamp to end the downtime.
id (int) – The downtime ID.
scope ([str], optional) – The scope(s) to which the downtime applies. Must be in key:value format. For example, host:app2. Provide multiple scopes as a comma-separated list like env:dev,env:prod. The resulting downtime applies to sources that matches ALL provided scopes ( env:dev AND env:prod ).
start (int, optional) – POSIX timestamp to start the downtime.

metric_content_encoding¶

class MetricContentEncoding(*args, **kwargs)¶

Bases: ModelSimple

HTTP header used to compress the media-type.

Parameters:

value (str) – If omitted defaults to “deflate”. Must be one of [“deflate”, “gzip”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

metric_metadata¶

class MetricMetadata(*args, **kwargs)¶

Bases: ModelNormal

Object with all metric related metadata.

Parameters:

description (str, optional) – Metric description.
integration (str, optional) – Name of the integration that sent the metric if applicable.
per_unit (str, optional) – Per unit of the metric such as second in bytes per second.
short_name (str, optional) – A more human-readable and abbreviated version of the metric name.
statsd_interval (int, optional) – StatsD flush interval of the metric in seconds if applicable.
type (str, optional) – Metric type such as gauge or rate.
unit (str, optional) – Primary unit of the metric such as byte or operation.

metric_search_response¶

class MetricSearchResponse(*args, **kwargs)¶

Bases: ModelNormal

Object containing the list of metrics matching the search query.

Parameters:: results (MetricSearchResponseResults, optional) – Search result.

metric_search_response_results¶

class MetricSearchResponseResults(*args, **kwargs)¶

Bases: ModelNormal

Search result.

Parameters:: metrics ([str], optional) – List of metrics that match the search query.

metrics_list_response¶

class MetricsListResponse(*args, **kwargs)¶

Bases: ModelNormal

Object listing all metric names stored by Datadog since a given time.

Parameters:

_from (str, optional) – Time when the metrics were active, seconds since the Unix epoch.
metrics ([str], optional) – List of metric names.

metrics_payload¶

class MetricsPayload(*args, **kwargs)¶

Bases: ModelNormal

The metrics’ payload.

Parameters:: series ([Series]) – A list of time series to submit to Datadog.

metrics_query_metadata¶

class MetricsQueryMetadata(*args, **kwargs)¶

Bases: ModelNormal

Object containing all metric names returned and their associated metadata.

Parameters:

aggr (str, none_type, optional) – Aggregation type.
display_name (str, optional) – Display name of the metric.
end (int, optional) – End of the time window, milliseconds since Unix epoch.
expression (str, optional) – Metric expression.
interval (int, optional) – Number of milliseconds between data samples.
length (int, optional) – Number of data samples.
metric (str, optional) – Metric name.
pointlist ([Point], optional) – List of points of the time series in milliseconds.
query_index (int, optional) – The index of the series’ query within the request.
scope (str, optional) – Metric scope, comma separated list of tags.
start (int, optional) – Start of the time window, milliseconds since Unix epoch.
tag_set ([str], optional) – Unique tags identifying this series.
unit ([MetricsQueryUnit, none_type], optional) – Detailed information about the metric unit. The first element describes the “primary unit” (for example, bytes in bytes per second ). The second element describes the “per unit” (for example, second in bytes per second ). If the second element is not present, the API returns null.

metrics_query_response¶

class MetricsQueryResponse(*args, **kwargs)¶

Bases: ModelNormal

Response Object that includes your query and the list of metrics retrieved.

Parameters:

error (str, optional) – Message indicating the errors if status is not ok.
from_date (int, optional) – Start of requested time window, milliseconds since Unix epoch.
group_by ([str], optional) – List of tag keys on which to group.
message (str, optional) – Message indicating success if status is ok.
query (str, optional) – Query string
res_type (str, optional) – Type of response.
series ([MetricsQueryMetadata], optional) – List of timeseries queried.
status (str, optional) – Status of the query.
to_date (int, optional) – End of requested time window, milliseconds since Unix epoch.

metrics_query_unit¶

class MetricsQueryUnit(*args, **kwargs)¶

Bases: ModelNormal

Object containing the metric unit family, scale factor, name, and short name.

Parameters:

family (str, optional) – Unit family, allows for conversion between units of the same family, for scaling.
name (str, optional) – Unit name
plural (str, optional) – Plural form of the unit name.
scale_factor (float, optional) – Factor for scaling between units of the same family.
short_name (str, optional) – Abbreviation of the unit.

monitor¶

class Monitor(*args, **kwargs)¶

Bases: ModelNormal

Object describing a monitor.

Parameters:

created (datetime, optional) – Timestamp of the monitor creation.
creator (Creator, optional) – Object describing the creator of the shared element.
deleted (datetime, none_type, optional) – Whether or not the monitor is deleted. (Always null )
id (int, optional) – ID of this monitor.
matching_downtimes ([MatchingDowntime], optional) – A list of active v1 downtimes that match this monitor.
message (str, optional) – A message to include with notifications for this monitor.
modified (datetime, optional) – Last timestamp when the monitor was edited.
multi (bool, optional) – Whether or not the monitor is broken down on different groups.
name (str, optional) – The monitor name.
options (MonitorOptions, optional) – List of options associated with your monitor.
overall_state (MonitorOverallStates, optional) – The different states your monitor can be in.
priority (int, none_type, optional) – Integer from 1 (high) to 5 (low) indicating alert severity.
query (str) – The monitor query.
restricted_roles ([str], none_type, optional) – A list of unique role identifiers to define which roles are allowed to edit the monitor. The unique identifiers for all roles can be pulled from the Roles API and are located in the data.id field. Editing a monitor includes any updates to the monitor configuration, monitor deletion, and muting of the monitor for any amount of time. restricted_roles is the successor of locked. For more information about locked and restricted_roles , see the monitor options docs.
state (MonitorState, optional) – Wrapper object with the different monitor states.
tags ([str], optional) – Tags associated to your monitor.
type (MonitorType) – The type of the monitor. For more information about type , see the monitor options docs.

monitor_device_id¶

class MonitorDeviceID(*args, **kwargs)¶

Bases: ModelSimple

ID of the device the Synthetics monitor is running on. Same as SyntheticsDeviceID.

Parameters:

value (str) – Must be one of [“laptop_large”, “tablet”, “mobile_small”, “chrome.laptop_large”, “chrome.tablet”, “chrome.mobile_small”, “firefox.laptop_large”, “firefox.tablet”, “firefox.mobile_small”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

monitor_formula_and_function_event_aggregation¶

class MonitorFormulaAndFunctionEventAggregation(*args, **kwargs)¶

Bases: ModelSimple

Aggregation methods for event platform queries.

Parameters:

value (str) – Must be one of [“count”, “cardinality”, “median”, “pc75”, “pc90”, “pc95”, “pc98”, “pc99”, “sum”, “min”, “max”, “avg”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

monitor_formula_and_function_event_query_definition¶

class MonitorFormulaAndFunctionEventQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

A formula and functions events query.

Parameters:

compute (MonitorFormulaAndFunctionEventQueryDefinitionCompute) – Compute options.
data_source (MonitorFormulaAndFunctionEventsDataSource) – Data source for event platform-based queries.
group_by ([MonitorFormulaAndFunctionEventQueryGroupBy], optional) – Group by options.
indexes ([str], optional) – An array of index names to query in the stream. Omit or use [] to query all indexes at once.
name (str) – Name of the query for use in formulas.
search (MonitorFormulaAndFunctionEventQueryDefinitionSearch, optional) – Search options.

monitor_formula_and_function_event_query_definition_compute¶

class MonitorFormulaAndFunctionEventQueryDefinitionCompute(*args, **kwargs)¶

Bases: ModelNormal

Compute options.

Parameters:

aggregation (MonitorFormulaAndFunctionEventAggregation) – Aggregation methods for event platform queries.
interval (int, optional) – A time interval in milliseconds.
metric (str, optional) – Measurable attribute to compute.

monitor_formula_and_function_event_query_definition_search¶

class MonitorFormulaAndFunctionEventQueryDefinitionSearch(*args, **kwargs)¶

Bases: ModelNormal

Search options.

Parameters:: query (str) – Events search string.

monitor_formula_and_function_event_query_group_by¶

class MonitorFormulaAndFunctionEventQueryGroupBy(*args, **kwargs)¶

Bases: ModelNormal

List of objects used to group by.

Parameters:

facet (str) – Event facet.
limit (int, optional) – Number of groups to return.
sort (MonitorFormulaAndFunctionEventQueryGroupBySort, optional) – Options for sorting group by results.

monitor_formula_and_function_event_query_group_by_sort¶

class MonitorFormulaAndFunctionEventQueryGroupBySort(*args, **kwargs)¶

Bases: ModelNormal

Options for sorting group by results.

Parameters:

aggregation (MonitorFormulaAndFunctionEventAggregation) – Aggregation methods for event platform queries.
metric (str, optional) – Metric used for sorting group by results.
order (QuerySortOrder, optional) – Direction of sort.

monitor_formula_and_function_events_data_source¶

class MonitorFormulaAndFunctionEventsDataSource(*args, **kwargs)¶

Bases: ModelSimple

Data source for event platform-based queries.

Parameters:

value (str) – Must be one of [“rum”, “ci_pipelines”, “ci_tests”, “audit”, “events”, “logs”, “spans”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

monitor_formula_and_function_query_definition¶

class MonitorFormulaAndFunctionQueryDefinition(*args, **kwargs)¶

Bases: ModelComposed

A formula and function query.

Parameters:

compute (MonitorFormulaAndFunctionEventQueryDefinitionCompute) – Compute options.
data_source (MonitorFormulaAndFunctionEventsDataSource) – Data source for event platform-based queries.
group_by ([MonitorFormulaAndFunctionEventQueryGroupBy], optional) – Group by options.
indexes ([str], optional) – An array of index names to query in the stream. Omit or use [] to query all indexes at once.
name (str) – Name of the query for use in formulas.
search (MonitorFormulaAndFunctionEventQueryDefinitionSearch, optional) – Search options.

monitor_group_search_response¶

class MonitorGroupSearchResponse(*args, **kwargs)¶

Bases: ModelNormal

The response of a monitor group search.

Parameters:

counts (MonitorGroupSearchResponseCounts, optional) – The counts of monitor groups per different criteria.
groups ([MonitorGroupSearchResult], optional) – The list of found monitor groups.
metadata (MonitorSearchResponseMetadata, optional) – Metadata about the response.

monitor_group_search_response_counts¶

class MonitorGroupSearchResponseCounts(*args, **kwargs)¶

Bases: ModelNormal

The counts of monitor groups per different criteria.

Parameters:

status (MonitorSearchCount, optional) – Search facets.
type (MonitorSearchCount, optional) – Search facets.

monitor_group_search_result¶

class MonitorGroupSearchResult(*args, **kwargs)¶

Bases: ModelNormal

A single monitor group search result.

Parameters:

group (str, optional) – The name of the group.
group_tags ([str], optional) – The list of tags of the monitor group.
last_nodata_ts (int, optional) – Latest timestamp the monitor group was in NO_DATA state.
last_triggered_ts (int, none_type, optional) – Latest timestamp the monitor group triggered.
monitor_id (int, optional) – The ID of the monitor.
monitor_name (str, optional) – The name of the monitor.
status (MonitorOverallStates, optional) – The different states your monitor can be in.

monitor_options¶

class MonitorOptions(*args, **kwargs)¶

Bases: ModelNormal

List of options associated with your monitor.

Parameters:

aggregation (MonitorOptionsAggregation, optional) – Type of aggregation performed in the monitor query.
device_ids ([MonitorDeviceID], optional) – IDs of the device the Synthetics monitor is running on. Deprecated.
enable_logs_sample (bool, optional) – Whether or not to send a log sample when the log monitor triggers.
enable_samples (bool, optional) – Whether or not to send a list of samples when the monitor triggers. This is only used by CI Test and Pipeline monitors.
escalation_message (str, optional) – We recommend using the is_renotify , block in the original message instead. A message to include with a re-notification. Supports the @username notification we allow elsewhere. Not applicable if renotify_interval is None.
evaluation_delay (int, none_type, optional) – Time (in seconds) to delay evaluation, as a non-negative integer. For example, if the value is set to 300 (5min), the timeframe is set to last_5m and the time is 7:00, the monitor evaluates data from 6:50 to 6:55. This is useful for AWS CloudWatch and other backfilled metrics to ensure the monitor always has data during evaluation.
group_retention_duration (str, optional) – The time span after which groups with missing data are dropped from the monitor state. The minimum value is one hour, and the maximum value is 72 hours. Example values are: “60m”, “1h”, and “2d”. This option is only available for APM Trace Analytics, Audit Trail, CI, Error Tracking, Event, Logs, and RUM monitors.
groupby_simple_monitor (bool, optional) – Whether the log alert monitor triggers a single alert or multiple alerts when any group breaches a threshold.
include_tags (bool, optional) –
A Boolean indicating whether notifications from this monitor automatically inserts its triggering tags into the title.

Examples
- If True , [Triggered on {host:h1}] Monitor Title
- If False , [Triggered] Monitor Title
locked (bool, optional) – Whether or not the monitor is locked (only editable by creator and admins). Use restricted_roles instead. Deprecated.
min_failure_duration (int, none_type, optional) – How long the test should be in failure before alerting (integer, number of seconds, max 7200).
min_location_failed (int, none_type, optional) – The minimum number of locations in failure at the same time during at least one moment in the min_failure_duration period ( min_location_failed and min_failure_duration are part of the advanced alerting rules - integer, >= 1).
new_group_delay (int, none_type, optional) –
Time (in seconds) to skip evaluations for new groups.

For example, this option can be used to skip evaluations for new hosts while they initialize.

Must be a non negative integer.
new_host_delay (int, none_type, optional) –
Time (in seconds) to allow a host to boot and applications to fully start before starting the evaluation of monitor results. Should be a non negative integer.

Use new_group_delay instead. Deprecated.
no_data_timeframe (int, none_type, optional) – The number of minutes before a monitor notifies after data stops reporting. Datadog recommends at least 2x the monitor timeframe for query alerts or 2 minutes for service checks. If omitted, 2x the evaluation timeframe is used for query alerts, and 24 hours is used for service checks.
notification_preset_name (MonitorOptionsNotificationPresets, optional) – Toggles the display of additional content sent in the monitor notification.
notify_audit (bool, optional) – A Boolean indicating whether tagged users is notified on changes to this monitor.
notify_by ([str], optional) – Controls what granularity a monitor alerts on. Only available for monitors with groupings. For instance, a monitor grouped by cluster , namespace , and pod can be configured to only notify on each new cluster violating the alert conditions by setting notify_by to ["cluster"]. Tags mentioned in notify_by must be a subset of the grouping tags in the query. For example, a query grouped by cluster and namespace cannot notify on region. Setting notify_by to [*] configures the monitor to notify as a simple-alert.
notify_no_data (bool, optional) – A Boolean indicating whether this monitor notifies when data stops reporting. Defaults to false.
on_missing_data (OnMissingDataOption, optional) – Controls how groups or monitors are treated if an evaluation does not return any data points. The default option results in different behavior depending on the monitor query type. For monitors using Count queries, an empty monitor evaluation is treated as 0 and is compared to the threshold conditions. For monitors using any query type other than Count, for example Gauge, Measure, or Rate, the monitor shows the last known status. This option is only available for APM Trace Analytics, Audit Trail, CI, Error Tracking, Event, Logs, and RUM monitors.
renotify_interval (int, none_type, optional) – The number of minutes after the last notification before a monitor re-notifies on the current status. It only re-notifies if it’s not resolved.
renotify_occurrences (int, none_type, optional) – The number of times re-notification messages should be sent on the current status at the provided re-notification interval.
renotify_statuses ([MonitorRenotifyStatusType], none_type, optional) – The types of monitor statuses for which re-notification messages are sent.
require_full_window (bool, optional) – A Boolean indicating whether this monitor needs a full window of data before it’s evaluated. We highly recommend you set this to false for sparse metrics, otherwise some evaluations are skipped. Default is false.
scheduling_options (MonitorOptionsSchedulingOptions, optional) – Configuration options for scheduling.
silenced ({str: (int, none_type,)}, optional) – Information about the downtime applied to the monitor. Only shows v1 downtimes. Deprecated.
synthetics_check_id (str, none_type, optional) – ID of the corresponding Synthetic check. Deprecated.
threshold_windows (MonitorThresholdWindowOptions, optional) – Alerting time window options.
thresholds (MonitorThresholds, optional) – List of the different monitor threshold available.
timeout_h (int, none_type, optional) – The number of hours of the monitor not reporting data before it automatically resolves from a triggered state. The minimum allowed value is 0 hours. The maximum allowed value is 24 hours.
variables ([MonitorFormulaAndFunctionQueryDefinition], optional) – List of requests that can be used in the monitor query. This feature is currently in beta.

monitor_options_aggregation¶

class MonitorOptionsAggregation(*args, **kwargs)¶

Bases: ModelNormal

Type of aggregation performed in the monitor query.

Parameters:

group_by (str, optional) – Group to break down the monitor on.
metric (str, optional) – Metric name used in the monitor.
type (str, optional) – Metric type used in the monitor.

monitor_options_custom_schedule¶

class MonitorOptionsCustomSchedule(*args, **kwargs)¶

Bases: ModelNormal

Configuration options for the custom schedule. This feature is in private beta.

Parameters:: recurrences ([MonitorOptionsCustomScheduleRecurrence], optional) – Array of custom schedule recurrences.

monitor_options_custom_schedule_recurrence¶

class MonitorOptionsCustomScheduleRecurrence(*args, **kwargs)¶

Bases: ModelNormal

Configuration for a recurrence set on the monitor options for custom schedule.

Parameters:

rrule (str, optional) – Defines the recurrence rule (RRULE) for a given schedule.
start (str, optional) – Defines the start date and time of the recurring schedule.
timezone (str, optional) – Defines the timezone the schedule runs on.

monitor_options_notification_presets¶

class MonitorOptionsNotificationPresets(*args, **kwargs)¶

Bases: ModelSimple

Toggles the display of additional content sent in the monitor notification.

Parameters:

value (str) – If omitted defaults to “show_all”. Must be one of [“show_all”, “hide_query”, “hide_handles”, “hide_all”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

monitor_options_scheduling_options¶

class MonitorOptionsSchedulingOptions(*args, **kwargs)¶

Bases: ModelNormal

Configuration options for scheduling.

Parameters:

custom_schedule (MonitorOptionsCustomSchedule, optional) – Configuration options for the custom schedule. This feature is in private beta.
evaluation_window (MonitorOptionsSchedulingOptionsEvaluationWindow, optional) – Configuration options for the evaluation window. If hour_starts is set, no other fields may be set. Otherwise, day_starts and month_starts must be set together.

monitor_options_scheduling_options_evaluation_window¶

class MonitorOptionsSchedulingOptionsEvaluationWindow(*args, **kwargs)¶

Bases: ModelNormal

Configuration options for the evaluation window. If hour_starts is set, no other fields may be set. Otherwise, day_starts and month_starts must be set together.

Parameters:

day_starts (str, optional) – The time of the day at which a one day cumulative evaluation window starts. Must be defined in UTC time in HH:mm format.
hour_starts (int, optional) – The minute of the hour at which a one hour cumulative evaluation window starts.
month_starts (int, optional) – The day of the month at which a one month cumulative evaluation window starts.

monitor_overall_states¶

class MonitorOverallStates(*args, **kwargs)¶

Bases: ModelSimple

The different states your monitor can be in.

Parameters:

value (str) – Must be one of [“Alert”, “Ignored”, “No Data”, “OK”, “Skipped”, “Unknown”, “Warn”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

monitor_renotify_status_type¶

class MonitorRenotifyStatusType(*args, **kwargs)¶

Bases: ModelSimple

The different statuses for which renotification is supported.

Parameters:

value (str) – Must be one of [“alert”, “warn”, “no data”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

monitor_search_count¶

class MonitorSearchCount(*args, **kwargs)¶

Bases: ModelSimple

Search facets.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

monitor_search_count_item¶

class MonitorSearchCountItem(*args, **kwargs)¶

Bases: ModelNormal

A facet item.

Parameters:

count (int, optional) – The number of found monitors with the listed value.
name (bool, date, datetime, dict, float, int, list, str, UUID, none_type, optional) – The facet value.

monitor_search_response¶

class MonitorSearchResponse(*args, **kwargs)¶

Bases: ModelNormal

The response form a monitor search.

Parameters:

counts (MonitorSearchResponseCounts, optional) – The counts of monitors per different criteria.
metadata (MonitorSearchResponseMetadata, optional) – Metadata about the response.
monitors ([MonitorSearchResult], optional) – The list of found monitors.

monitor_search_response_counts¶

class MonitorSearchResponseCounts(*args, **kwargs)¶

Bases: ModelNormal

The counts of monitors per different criteria.

Parameters:

muted (MonitorSearchCount, optional) – Search facets.
status (MonitorSearchCount, optional) – Search facets.
tag (MonitorSearchCount, optional) – Search facets.
type (MonitorSearchCount, optional) – Search facets.

monitor_search_response_metadata¶

class MonitorSearchResponseMetadata(*args, **kwargs)¶

Bases: ModelNormal

Metadata about the response.

Parameters:

page (int, optional) – The page to start paginating from.
page_count (int, optional) – The number of pages.
per_page (int, optional) – The number of monitors to return per page.
total_count (int, optional) – The total number of monitors.

monitor_search_result¶

class MonitorSearchResult(*args, **kwargs)¶

Bases: ModelNormal

Holds search results.

Parameters:

classification (str, optional) – Classification of the monitor.
creator (Creator, optional) – Object describing the creator of the shared element.
id (int, optional) – ID of the monitor.
last_triggered_ts (int, none_type, optional) – Latest timestamp the monitor triggered.
metrics ([str], optional) – Metrics used by the monitor.
name (str, optional) – The monitor name.
notifications ([MonitorSearchResultNotification], optional) – The notification triggered by the monitor.
org_id (int, optional) – The ID of the organization.
query (str, optional) – The monitor query.
scopes ([str], optional) – The scope(s) to which the downtime applies, for example host:app2. Provide multiple scopes as a comma-separated list, for example env:dev,env:prod. The resulting downtime applies to sources that matches ALL provided scopes (that is env:dev AND env:prod ), NOT any of them.
status (MonitorOverallStates, optional) – The different states your monitor can be in.
tags ([str], optional) – Tags associated with the monitor.
type (MonitorType, optional) –
The type of the monitor. For more information about type , see the monitor options docs.

monitor_search_result_notification¶

class MonitorSearchResultNotification(*args, **kwargs)¶

Bases: ModelNormal

A notification triggered by the monitor.

Parameters:

handle (str, optional) – The email address that received the notification.
name (str, optional) – The username receiving the notification

monitor_state¶

class MonitorState(*args, **kwargs)¶

Bases: ModelNormal

Wrapper object with the different monitor states.

Parameters:: groups ({str: (MonitorStateGroup,)}, optional) – Dictionary where the keys are groups (comma separated lists of tags) and the values are the list of groups your monitor is broken down on.

monitor_state_group¶

class MonitorStateGroup(*args, **kwargs)¶

Bases: ModelNormal

Monitor state for a single group.

Parameters:

last_nodata_ts (int, optional) – Latest timestamp the monitor was in NO_DATA state.
last_notified_ts (int, optional) – Latest timestamp of the notification sent for this monitor group.
last_resolved_ts (int, optional) – Latest timestamp the monitor group was resolved.
last_triggered_ts (int, optional) – Latest timestamp the monitor group triggered.
name (str, optional) – The name of the monitor.
status (MonitorOverallStates, optional) – The different states your monitor can be in.

monitor_summary_widget_definition¶

class MonitorSummaryWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The monitor summary widget displays a summary view of all your Datadog monitors, or a subset based on a query. Only available on FREE layout dashboards.

Parameters:

color_preference (WidgetColorPreference, optional) – Which color to use on the widget.
count (int, optional) – The number of monitors to display. Deprecated.
display_format (WidgetMonitorSummaryDisplayFormat, optional) – What to display on the widget.
hide_zero_counts (bool, optional) – Whether to show counts of 0 or not.
query (str) – Query to filter the monitors with.
show_last_triggered (bool, optional) – Whether to show the time that has elapsed since the monitor/group triggered.
show_priority (bool, optional) – Whether to show the priorities column.
sort (WidgetMonitorSummarySort, optional) – Widget sorting methods.
start (int, optional) – The start of the list. Typically 0. Deprecated.
summary_type (WidgetSummaryType, optional) – Which summary type should be used.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (MonitorSummaryWidgetDefinitionType) – Type of the monitor summary widget.

monitor_summary_widget_definition_type¶

class MonitorSummaryWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the monitor summary widget.

Parameters:

value (str) – If omitted defaults to “manage_status”. Must be one of [“manage_status”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

monitor_threshold_window_options¶

class MonitorThresholdWindowOptions(*args, **kwargs)¶

Bases: ModelNormal

Alerting time window options.

Parameters:

recovery_window (str, none_type, optional) – Describes how long an anomalous metric must be normal before the alert recovers.
trigger_window (str, none_type, optional) – Describes how long a metric must be anomalous before an alert triggers.

monitor_thresholds¶

class MonitorThresholds(*args, **kwargs)¶

Bases: ModelNormal

List of the different monitor threshold available.

Parameters:

critical (float, optional) – The monitor CRITICAL threshold.
critical_recovery (float, none_type, optional) – The monitor CRITICAL recovery threshold.
ok (float, none_type, optional) – The monitor OK threshold.
unknown (float, none_type, optional) – The monitor UNKNOWN threshold.
warning (float, none_type, optional) – The monitor WARNING threshold.
warning_recovery (float, none_type, optional) – The monitor WARNING recovery threshold.

monitor_type¶

class MonitorType(*args, **kwargs)¶

Bases: ModelSimple

The type of the monitor. For more information about type, see the [monitor options](https://docs.datadoghq.com/monitors/guide/monitor_api_options/) docs.

Parameters:

value (str) – Must be one of [“composite”, “event alert”, “log alert”, “metric alert”, “process alert”, “query alert”, “rum alert”, “service check”, “synthetics alert”, “trace-analytics alert”, “slo alert”, “event-v2 alert”, “audit alert”, “ci-pipelines alert”, “ci-tests alert”, “error-tracking alert”, “database-monitoring alert”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

monitor_update_request¶

class MonitorUpdateRequest(*args, **kwargs)¶

Bases: ModelNormal

Object describing a monitor update request.

Parameters:

created (datetime, optional) – Timestamp of the monitor creation.
creator (Creator, optional) – Object describing the creator of the shared element.
deleted (datetime, none_type, optional) – Whether or not the monitor is deleted. (Always null )
id (int, optional) – ID of this monitor.
message (str, optional) – A message to include with notifications for this monitor.
modified (datetime, optional) – Last timestamp when the monitor was edited.
multi (bool, optional) – Whether or not the monitor is broken down on different groups.
name (str, optional) – The monitor name.
options (MonitorOptions, optional) – List of options associated with your monitor.
overall_state (MonitorOverallStates, optional) – The different states your monitor can be in.
priority (int, optional) – Integer from 1 (high) to 5 (low) indicating alert severity.
query (str, optional) – The monitor query.
restricted_roles ([str], none_type, optional) –
A list of unique role identifiers to define which roles are allowed to edit the monitor. The unique identifiers for all roles can be pulled from the Roles API and are located in the data.id field. Editing a monitor includes any updates to the monitor configuration, monitor deletion, and muting of the monitor for any amount of time. restricted_roles is the successor of locked. For more information about locked and restricted_roles , see the monitor options docs.
state (MonitorState, optional) – Wrapper object with the different monitor states.
tags ([str], optional) – Tags associated to your monitor.
type (MonitorType, optional) –
The type of the monitor. For more information about type , see the monitor options docs.

monthly_usage_attribution_body¶

class MonthlyUsageAttributionBody(*args, **kwargs)¶

Bases: ModelNormal

Usage Summary by tag for a given organization.

Parameters:

month (datetime, optional) – Datetime in ISO-8601 format, UTC, precise to month: [YYYY-MM].
org_name (str, optional) – The name of the organization.
public_id (str, optional) – The organization public ID.
region (str, optional) – The region of the Datadog instance that the organization belongs to.
tag_config_source (str, optional) – The source of the usage attribution tag configuration and the selected tags in the format <source_org_name>:::<selected tag 1>///<selected tag 2>///<selected tag 3>.
tags (UsageAttributionTagNames, none_type, optional) –
Tag keys and values.

A null value here means that the requested tag breakdown cannot be applied because it does not match the tags configured for usage attribution. In this scenario the API returns the total usage, not broken down by tags.
updated_at (datetime, optional) – Datetime of the most recent update to the usage values.
values (MonthlyUsageAttributionValues, optional) – Fields in Usage Summary by tag(s).

monthly_usage_attribution_metadata¶

class MonthlyUsageAttributionMetadata(*args, **kwargs)¶

Bases: ModelNormal

The object containing document metadata.

Parameters:

aggregates (UsageAttributionAggregates, optional) – An array of available aggregates.
pagination (MonthlyUsageAttributionPagination, optional) – The metadata for the current pagination.

monthly_usage_attribution_pagination¶

class MonthlyUsageAttributionPagination(*args, **kwargs)¶

Bases: ModelNormal

The metadata for the current pagination.

Parameters:: next_record_id (str, none_type, optional) – The cursor to use to get the next results, if any. To make the next request, use the same parameters with the addition of the next_record_id.

monthly_usage_attribution_response¶

class MonthlyUsageAttributionResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the monthly Usage Summary by tag(s).

Parameters:

metadata (MonthlyUsageAttributionMetadata, optional) – The object containing document metadata.
usage ([MonthlyUsageAttributionBody], optional) – Get usage summary by tag(s).

monthly_usage_attribution_supported_metrics¶

class MonthlyUsageAttributionSupportedMetrics(*args, **kwargs)¶

Bases: ModelSimple

Supported metrics for monthly usage attribution requests.

Parameters:

value (str) – Must be one of [“api_usage”, “api_percentage”, “apm_fargate_usage”, “apm_fargate_percentage”, “appsec_fargate_usage”, “appsec_fargate_percentage”, “apm_host_usage”, “apm_host_percentage”, “apm_usm_usage”, “apm_usm_percentage”, “appsec_usage”, “appsec_percentage”, “browser_usage”, “browser_percentage”, “ci_visibility_itr_usage”, “ci_visibility_itr_percentage”, “cloud_siem_usage”, “cloud_siem_percentage”, “container_excl_agent_usage”, “container_excl_agent_percentage”, “container_usage”, “container_percentage”, “cspm_containers_percentage”, “cspm_containers_usage”, “cspm_hosts_percentage”, “cspm_hosts_usage”, “custom_timeseries_usage”, “custom_timeseries_percentage”, “custom_ingested_timeseries_usage”, “custom_ingested_timeseries_percentage”, “cws_containers_percentage”, “cws_containers_usage”, “cws_hosts_percentage”, “cws_hosts_usage”, “dbm_hosts_percentage”, “dbm_hosts_usage”, “dbm_queries_percentage”, “dbm_queries_usage”, “estimated_indexed_logs_usage”, “estimated_indexed_logs_percentage”, “estimated_ingested_logs_usage”, “estimated_ingested_logs_percentage”, “estimated_indexed_spans_usage”, “estimated_indexed_spans_percentage”, “estimated_ingested_spans_usage”, “estimated_ingested_spans_percentage”, “fargate_usage”, “fargate_percentage”, “functions_usage”, “functions_percentage”, “infra_host_usage”, “infra_host_percentage”, “invocations_usage”, “invocations_percentage”, “lambda_traced_invocations_usage”, “lambda_traced_invocations_percentage”, “mobile_app_testing_percentage”, “mobile_app_testing_usage”, “ndm_netflow_usage”, “ndm_netflow_percentage”, “npm_host_usage”, “npm_host_percentage”, “obs_pipeline_bytes_usage”, “obs_pipeline_bytes_percentage”, “profiled_container_usage”, “profiled_container_percentage”, “profiled_fargate_usage”, “profiled_fargate_percentage”, “profiled_host_usage”, “profiled_host_percentage”, “serverless_apps_usage”, “serverless_apps_percentage”, “snmp_usage”, “snmp_percentage”, “estimated_rum_sessions_usage”, “estimated_rum_sessions_percentage”, “universal_service_monitoring_usage”, “universal_service_monitoring_percentage”, “vuln_management_hosts_usage”, “vuln_management_hosts_percentage”, “sds_scanned_bytes_usage”, “sds_scanned_bytes_percentage”, “ci_test_indexed_spans_usage”, “ci_test_indexed_spans_percentage”, “ingested_logs_bytes_usage”, “ingested_logs_bytes_percentage”, “ci_pipeline_indexed_spans_usage”, “ci_pipeline_indexed_spans_percentage”, “indexed_spans_usage”, “indexed_spans_percentage”, “custom_event_usage”, “custom_event_percentage”, “logs_indexed_custom_retention_usage”, “logs_indexed_custom_retention_percentage”, “logs_indexed_360day_usage”, “logs_indexed_360day_percentage”, “logs_indexed_180day_usage”, “logs_indexed_180day_percentage”, “logs_indexed_90day_usage”, “logs_indexed_90day_percentage”, “logs_indexed_60day_usage”, “logs_indexed_60day_percentage”, “logs_indexed_45day_usage”, “logs_indexed_45day_percentage”, “logs_indexed_30day_usage”, “logs_indexed_30day_percentage”, “logs_indexed_15day_usage”, “logs_indexed_15day_percentage”, “logs_indexed_7day_usage”, “logs_indexed_7day_percentage”, “logs_indexed_3day_usage”, “logs_indexed_3day_percentage”, “rum_replay_sessions_usage”, “rum_replay_sessions_percentage”, “rum_browser_mobile_sessions_usage”, “rum_browser_mobile_sessions_percentage”, “ingested_spans_bytes_usage”, “ingested_spans_bytes_percentage”, “siem_ingested_bytes_usage”, “siem_ingested_bytes_percentage”, “*”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

monthly_usage_attribution_values¶

class MonthlyUsageAttributionValues(*args, **kwargs)¶

Bases: ModelNormal

Fields in Usage Summary by tag(s).

Parameters:

api_percentage (float, optional) – The percentage of synthetic API test usage by tag(s).
api_usage (float, optional) – The synthetic API test usage by tag(s).
apm_fargate_percentage (float, optional) – The percentage of APM ECS Fargate task usage by tag(s).
apm_fargate_usage (float, optional) – The APM ECS Fargate task usage by tag(s).
apm_host_percentage (float, optional) – The percentage of APM host usage by tag(s).
apm_host_usage (float, optional) – The APM host usage by tag(s).
apm_usm_percentage (float, optional) – The percentage of APM and Universal Service Monitoring host usage by tag(s).
apm_usm_usage (float, optional) – The APM and Universal Service Monitoring host usage by tag(s).
appsec_fargate_percentage (float, optional) – The percentage of Application Security Monitoring ECS Fargate task usage by tag(s).
appsec_fargate_usage (float, optional) – The Application Security Monitoring ECS Fargate task usage by tag(s).
appsec_percentage (float, optional) – The percentage of Application Security Monitoring host usage by tag(s).
appsec_usage (float, optional) – The Application Security Monitoring host usage by tag(s).
browser_percentage (float, optional) – The percentage of synthetic browser test usage by tag(s).
browser_usage (float, optional) – The synthetic browser test usage by tag(s).
ci_pipeline_indexed_spans_percentage (float, optional) – The percentage of CI Pipeline Indexed Spans usage by tag(s).
ci_pipeline_indexed_spans_usage (float, optional) – The total CI Pipeline Indexed Spans usage by tag(s).
ci_test_indexed_spans_percentage (float, optional) – The percentage of CI Test Indexed Spans usage by tag(s).
ci_test_indexed_spans_usage (float, optional) – The total CI Test Indexed Spans usage by tag(s).
ci_visibility_itr_percentage (float, optional) – The percentage of Git committers for Intelligent Test Runner usage by tag(s).
ci_visibility_itr_usage (float, optional) – The Git committers for Intelligent Test Runner usage by tag(s).
cloud_siem_percentage (float, optional) – The percentage of Cloud Security Information and Event Management usage by tag(s).
cloud_siem_usage (float, optional) – The Cloud Security Information and Event Management usage by tag(s).
container_excl_agent_percentage (float, optional) – The percentage of container usage without the Datadog Agent by tag(s).
container_excl_agent_usage (float, optional) – The container usage without the Datadog Agent by tag(s).
container_percentage (float, optional) – The percentage of container usage by tag(s).
container_usage (float, optional) – The container usage by tag(s).
cspm_containers_percentage (float, optional) – The percentage of Cloud Security Management Pro container usage by tag(s).
cspm_containers_usage (float, optional) – The Cloud Security Management Pro container usage by tag(s).
cspm_hosts_percentage (float, optional) – The percentage of Cloud Security Management Pro host usage by tag(s).
cspm_hosts_usage (float, optional) – The Cloud Security Management Pro host usage by tag(s).
custom_event_percentage (float, optional) – The percentage of Custom Events usage by tag(s).
custom_event_usage (float, optional) – The total Custom Events usage by tag(s).
custom_ingested_timeseries_percentage (float, optional) – The percentage of ingested custom metrics usage by tag(s).
custom_ingested_timeseries_usage (float, optional) – The ingested custom metrics usage by tag(s).
custom_timeseries_percentage (float, optional) – The percentage of indexed custom metrics usage by tag(s).
custom_timeseries_usage (float, optional) – The indexed custom metrics usage by tag(s).
cws_containers_percentage (float, optional) – The percentage of Cloud Workload Security container usage by tag(s).
cws_containers_usage (float, optional) – The Cloud Workload Security container usage by tag(s).
cws_hosts_percentage (float, optional) – The percentage of Cloud Workload Security host usage by tag(s).
cws_hosts_usage (float, optional) – The Cloud Workload Security host usage by tag(s).
dbm_hosts_percentage (float, optional) – The percentage of Database Monitoring host usage by tag(s).
dbm_hosts_usage (float, optional) – The Database Monitoring host usage by tag(s).
dbm_queries_percentage (float, optional) – The percentage of Database Monitoring queries usage by tag(s).
dbm_queries_usage (float, optional) – The Database Monitoring queries usage by tag(s).
estimated_indexed_logs_percentage (float, optional) – The percentage of estimated live indexed logs usage by tag(s).
estimated_indexed_logs_usage (float, optional) – The estimated live indexed logs usage by tag(s).
estimated_indexed_spans_percentage (float, optional) – The percentage of estimated indexed spans usage by tag(s).
estimated_indexed_spans_usage (float, optional) – The estimated indexed spans usage by tag(s).
estimated_ingested_logs_percentage (float, optional) – The percentage of estimated live ingested logs usage by tag(s).
estimated_ingested_logs_usage (float, optional) – The estimated live ingested logs usage by tag(s).
estimated_ingested_spans_percentage (float, optional) – The percentage of estimated ingested spans usage by tag(s).
estimated_ingested_spans_usage (float, optional) – The estimated ingested spans usage by tag(s).
estimated_rum_sessions_percentage (float, optional) – The percentage of estimated rum sessions usage by tag(s).
estimated_rum_sessions_usage (float, optional) – The estimated rum sessions usage by tag(s).
fargate_percentage (float, optional) – The percentage of Fargate usage by tags.
fargate_usage (float, optional) – The Fargate usage by tags.
functions_percentage (float, optional) – The percentage of Lambda function usage by tag(s).
functions_usage (float, optional) – The Lambda function usage by tag(s).
indexed_spans_percentage (float, optional) – The percentage of APM Indexed Spans usage by tag(s).
indexed_spans_usage (float, optional) – The total APM Indexed Spans usage by tag(s).
infra_host_percentage (float, optional) – The percentage of infrastructure host usage by tag(s).
infra_host_usage (float, optional) – The infrastructure host usage by tag(s).
ingested_logs_bytes_percentage (float, optional) – The percentage of Ingested Logs usage by tag(s).
ingested_logs_bytes_usage (float, optional) – The total Ingested Logs usage by tag(s).
ingested_spans_bytes_percentage (float, optional) – The percentage of APM Ingested Spans usage by tag(s).
ingested_spans_bytes_usage (float, optional) – The total APM Ingested Spans usage by tag(s).
invocations_percentage (float, optional) – The percentage of Lambda invocation usage by tag(s).
invocations_usage (float, optional) – The Lambda invocation usage by tag(s).
lambda_traced_invocations_percentage (float, optional) – The percentage of Serverless APM usage by tag(s).
lambda_traced_invocations_usage (float, optional) – The Serverless APM usage by tag(s).
logs_indexed_15day_percentage (float, optional) – The percentage of Indexed Logs (15-day Retention) usage by tag(s).
logs_indexed_15day_usage (float, optional) – The total Indexed Logs (15-day Retention) usage by tag(s).
logs_indexed_180day_percentage (float, optional) – The percentage of Indexed Logs (180-day Retention) usage by tag(s).
logs_indexed_180day_usage (float, optional) – The total Indexed Logs (180-day Retention) usage by tag(s).
logs_indexed_30day_percentage (float, optional) – The percentage of Indexed Logs (30-day Retention) usage by tag(s).
logs_indexed_30day_usage (float, optional) – The total Indexed Logs (30-day Retention) usage by tag(s).
logs_indexed_360day_percentage (float, optional) – The percentage of Indexed Logs (360-day Retention) usage by tag(s).
logs_indexed_360day_usage (float, optional) – The total Indexed Logs (360-day Retention) usage by tag(s).
logs_indexed_3day_percentage (float, optional) – The percentage of Indexed Logs (3-day Retention) usage by tag(s).
logs_indexed_3day_usage (float, optional) – The total Indexed Logs (3-day Retention) usage by tag(s).
logs_indexed_45day_percentage (float, optional) – The percentage of Indexed Logs (45-day Retention) usage by tag(s).
logs_indexed_45day_usage (float, optional) – The total Indexed Logs (45-day Retention) usage by tag(s).
logs_indexed_60day_percentage (float, optional) – The percentage of Indexed Logs (60-day Retention) usage by tag(s).
logs_indexed_60day_usage (float, optional) – The total Indexed Logs (60-day Retention) usage by tag(s).
logs_indexed_7day_percentage (float, optional) – The percentage of Indexed Logs (7-day Retention) usage by tag(s).
logs_indexed_7day_usage (float, optional) – The total Indexed Logs (7-day Retention) usage by tag(s).
logs_indexed_90day_percentage (float, optional) – The percentage of Indexed Logs (90-day Retention) usage by tag(s).
logs_indexed_90day_usage (float, optional) – The total Indexed Logs (90-day Retention) usage by tag(s).
logs_indexed_custom_retention_percentage (float, optional) – The percentage of Indexed Logs (Custom Retention) usage by tag(s).
logs_indexed_custom_retention_usage (float, optional) – The total Indexed Logs (Custom Retention) usage by tag(s).
mobile_app_testing_percentage (float, optional) – The percentage of Synthetic mobile application test usage by tag(s).
mobile_app_testing_usage (float, optional) – The Synthetic mobile application test usage by tag(s).
ndm_netflow_percentage (float, optional) – The percentage of Network Device Monitoring NetFlow usage by tag(s).
ndm_netflow_usage (float, optional) – The Network Device Monitoring NetFlow usage by tag(s).
npm_host_percentage (float, optional) – The percentage of network host usage by tag(s).
npm_host_usage (float, optional) – The network host usage by tag(s).
obs_pipeline_bytes_percentage (float, optional) – The percentage of observability pipeline bytes usage by tag(s).
obs_pipeline_bytes_usage (float, optional) – The observability pipeline bytes usage by tag(s).
profiled_container_percentage (float, optional) – The percentage of profiled container usage by tag(s).
profiled_container_usage (float, optional) – The profiled container usage by tag(s).
profiled_fargate_percentage (float, optional) – The percentage of profiled Fargate task usage by tag(s).
profiled_fargate_usage (float, optional) – The profiled Fargate task usage by tag(s).
profiled_host_percentage (float, optional) – The percentage of profiled hosts usage by tag(s).
profiled_host_usage (float, optional) – The profiled hosts usage by tag(s).
rum_browser_mobile_sessions_percentage (float, optional) – The percentage of RUM Browser and Mobile usage by tag(s).
rum_browser_mobile_sessions_usage (float, optional) – The total RUM Browser and Mobile usage by tag(s).
rum_replay_sessions_percentage (float, optional) – The percentage of RUM Replay Sessions usage by tag(s).
rum_replay_sessions_usage (float, optional) – The total RUM Replay Sessions usage by tag(s).
sds_scanned_bytes_percentage (float, optional) – The percentage of Sensitive Data Scanner usage by tag(s).
sds_scanned_bytes_usage (float, optional) – The total Sensitive Data Scanner usage by tag(s).
serverless_apps_percentage (float, optional) – The percentage of Serverless Apps usage by tag(s).
serverless_apps_usage (float, optional) – The total Serverless Apps usage by tag(s).
siem_ingested_bytes_percentage (float, optional) – The percentage of SIEM usage by tag(s).
siem_ingested_bytes_usage (float, optional) – The total SIEM usage by tag(s).
snmp_percentage (float, optional) – The percentage of network device usage by tag(s).
snmp_usage (float, optional) – The network device usage by tag(s).
universal_service_monitoring_percentage (float, optional) – The percentage of universal service monitoring usage by tag(s).
universal_service_monitoring_usage (float, optional) – The universal service monitoring usage by tag(s).
vuln_management_hosts_percentage (float, optional) – The percentage of Application Vulnerability Management usage by tag(s).
vuln_management_hosts_usage (float, optional) – The Application Vulnerability Management usage by tag(s).

note_widget_definition¶

class NoteWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The notes and links widget is similar to free text widget, but allows for more formatting options.

Parameters:

background_color (str, optional) – Background color of the note.
content (str) – Content of the note.
font_size (str, optional) – Size of the text.
has_padding (bool, optional) – Whether to add padding or not.
show_tick (bool, optional) – Whether to show a tick or not.
text_align (WidgetTextAlign, optional) – How to align the text on the widget.
tick_edge (WidgetTickEdge, optional) – Define how you want to align the text on the widget.
tick_pos (str, optional) – Where to position the tick on an edge.
type (NoteWidgetDefinitionType) – Type of the note widget.
vertical_align (WidgetVerticalAlign, optional) – Vertical alignment.

note_widget_definition_type¶

class NoteWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the note widget.

Parameters:

value (str) – If omitted defaults to “note”. Must be one of [“note”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

notebook_absolute_time¶

class NotebookAbsoluteTime(*args, **kwargs)¶

Bases: ModelNormal

Absolute timeframe.

Parameters:

end (datetime) – The end time.
live (bool, optional) – Indicates whether the timeframe should be shifted to end at the current time.
start (datetime) – The start time.

notebook_author¶

class NotebookAuthor(*args, **kwargs)¶

Bases: ModelNormal

Attributes of user object returned by the API.

Parameters:

created_at (datetime, optional) – Creation time of the user.
disabled (bool, optional) – Whether the user is disabled.
email (str, optional) – Email of the user.
handle (str, optional) – Handle of the user.
icon (str, optional) – URL of the user’s icon.
name (str, none_type, optional) – Name of the user.
status (str, optional) – Status of the user.
title (str, none_type, optional) – Title of the user.
verified (bool, optional) – Whether the user is verified.

notebook_cell_create_request¶

class NotebookCellCreateRequest(*args, **kwargs)¶

Bases: ModelNormal

The description of a notebook cell create request.

Parameters:

attributes (NotebookCellCreateRequestAttributes) – The attributes of a notebook cell in create cell request. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.
type (NotebookCellResourceType) – Type of the Notebook Cell resource.

notebook_cell_create_request_attributes¶

class NotebookCellCreateRequestAttributes(*args, **kwargs)¶

Bases: ModelComposed

The attributes of a notebook cell in create cell request. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.

Parameters:

definition (NotebookMarkdownCellDefinition) – Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.
graph_size (NotebookGraphSize, optional) – The size of the graph.
split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.
time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

notebook_cell_resource_type¶

class NotebookCellResourceType(*args, **kwargs)¶

Bases: ModelSimple

Type of the Notebook Cell resource.

Parameters:

value (str) – If omitted defaults to “notebook_cells”. Must be one of [“notebook_cells”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

notebook_cell_response¶

class NotebookCellResponse(*args, **kwargs)¶

Bases: ModelNormal

The description of a notebook cell response.

Parameters:

attributes (NotebookCellResponseAttributes) –
The attributes of a notebook cell response. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.
id (str) – Notebook cell ID.
type (NotebookCellResourceType) – Type of the Notebook Cell resource.

notebook_cell_response_attributes¶

class NotebookCellResponseAttributes(*args, **kwargs)¶

Bases: ModelComposed

The attributes of a notebook cell response. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.

Parameters:

definition (NotebookMarkdownCellDefinition) – Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.
graph_size (NotebookGraphSize, optional) – The size of the graph.
split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.
time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

notebook_cell_time¶

class NotebookCellTime(*args, **kwargs)¶

Bases: ModelComposed

Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

Parameters:

live_span (WidgetLiveSpan) – The available timeframes depend on the widget you are using.
end (datetime) – The end time.
live (bool, optional) – Indicates whether the timeframe should be shifted to end at the current time.
start (datetime) – The start time.

notebook_cell_update_request¶

class NotebookCellUpdateRequest(*args, **kwargs)¶

Bases: ModelNormal

The description of a notebook cell update request.

Parameters:

attributes (NotebookCellUpdateRequestAttributes) –
The attributes of a notebook cell in update cell request. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.
id (str) – Notebook cell ID.
type (NotebookCellResourceType) – Type of the Notebook Cell resource.

notebook_cell_update_request_attributes¶

class NotebookCellUpdateRequestAttributes(*args, **kwargs)¶

Bases: ModelComposed

The attributes of a notebook cell in update cell request. Valid cell types are markdown , timeseries , toplist , heatmap , distribution , log_stream. More information on each graph visualization type.

Parameters:

definition (NotebookMarkdownCellDefinition) – Text in a notebook is formatted with [Markdown](https://daringfireball.net/projects/markdown/), which enables the use of headings, subheadings, links, images, lists, and code blocks.
graph_size (NotebookGraphSize, optional) – The size of the graph.
split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.
time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

notebook_create_data¶

class NotebookCreateData(*args, **kwargs)¶

Bases: ModelNormal

The data for a notebook create request.

Parameters:

attributes (NotebookCreateDataAttributes) – The data attributes of a notebook.
type (NotebookResourceType) – Type of the Notebook resource.

notebook_create_data_attributes¶

class NotebookCreateDataAttributes(*args, **kwargs)¶

Bases: ModelNormal

The data attributes of a notebook.

Parameters:

cells ([NotebookCellCreateRequest]) – List of cells to display in the notebook.
metadata (NotebookMetadata, optional) – Metadata associated with the notebook.
name (str) – The name of the notebook.
status (NotebookStatus, optional) – Publication status of the notebook. For now, always “published”.
time (NotebookGlobalTime) – Notebook global timeframe.

notebook_create_request¶

class NotebookCreateRequest(*args, **kwargs)¶

Bases: ModelNormal

The description of a notebook create request.

Parameters:: data (NotebookCreateData) – The data for a notebook create request.

notebook_distribution_cell_attributes¶

class NotebookDistributionCellAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attributes of a notebook distribution cell.

Parameters:

definition (DistributionWidgetDefinition) – The Distribution visualization is another way of showing metrics aggregated across one or several tags, such as hosts. Unlike the heat map, a distribution graph’s x-axis is quantity rather than time.
graph_size (NotebookGraphSize, optional) – The size of the graph.
split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.
time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

notebook_global_time¶

class NotebookGlobalTime(*args, **kwargs)¶

Bases: ModelComposed

Notebook global timeframe.

Parameters:

live_span (WidgetLiveSpan) – The available timeframes depend on the widget you are using.
end (datetime) – The end time.
live (bool, optional) – Indicates whether the timeframe should be shifted to end at the current time.
start (datetime) – The start time.

notebook_graph_size¶

class NotebookGraphSize(*args, **kwargs)¶

Bases: ModelSimple

The size of the graph.

Parameters:

value (str) – Must be one of [“xs”, “s”, “m”, “l”, “xl”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

notebook_heat_map_cell_attributes¶

class NotebookHeatMapCellAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attributes of a notebook heatmap cell.

Parameters:

definition (HeatMapWidgetDefinition) – The heat map visualization shows metrics aggregated across many tags, such as hosts. The more hosts that have a particular value, the darker that square is.
graph_size (NotebookGraphSize, optional) – The size of the graph.
split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.
time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

notebook_log_stream_cell_attributes¶

class NotebookLogStreamCellAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attributes of a notebook log_stream cell.

Parameters:

definition (LogStreamWidgetDefinition) – The Log Stream displays a log flow matching the defined query. Only available on FREE layout dashboards.
graph_size (NotebookGraphSize, optional) – The size of the graph.
time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

notebook_markdown_cell_attributes¶

class NotebookMarkdownCellAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attributes of a notebook markdown cell.

Parameters:: definition (NotebookMarkdownCellDefinition) – Text in a notebook is formatted with Markdown , which enables the use of headings, subheadings, links, images, lists, and code blocks.

notebook_markdown_cell_definition¶

class NotebookMarkdownCellDefinition(*args, **kwargs)¶

Bases: ModelNormal

Text in a notebook is formatted with Markdown , which enables the use of headings, subheadings, links, images, lists, and code blocks.

Parameters:

text (str) – The markdown content.
type (NotebookMarkdownCellDefinitionType) – Type of the markdown cell.

notebook_markdown_cell_definition_type¶

class NotebookMarkdownCellDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the markdown cell.

Parameters:

value (str) – If omitted defaults to “markdown”. Must be one of [“markdown”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

notebook_metadata¶

class NotebookMetadata(*args, **kwargs)¶

Bases: ModelNormal

Metadata associated with the notebook.

Parameters:

is_template (bool, optional) – Whether or not the notebook is a template.
take_snapshots (bool, optional) – Whether or not the notebook takes snapshot image backups of the notebook’s fixed-time graphs.
type (NotebookMetadataType, none_type, optional) – Metadata type of the notebook.

notebook_metadata_type¶

class NotebookMetadataType(*args, **kwargs)¶

Bases: ModelSimple

Metadata type of the notebook.

Parameters:

value (str) – Must be one of [“postmortem”, “runbook”, “investigation”, “documentation”, “report”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

notebook_relative_time¶

class NotebookRelativeTime(*args, **kwargs)¶

Bases: ModelNormal

Relative timeframe.

Parameters:: live_span (WidgetLiveSpan) – The available timeframes depend on the widget you are using.

notebook_resource_type¶

class NotebookResourceType(*args, **kwargs)¶

Bases: ModelSimple

Type of the Notebook resource.

Parameters:

value (str) – If omitted defaults to “notebooks”. Must be one of [“notebooks”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

notebook_response¶

class NotebookResponse(*args, **kwargs)¶

Bases: ModelNormal

The description of a notebook response.

Parameters:: data (NotebookResponseData, optional) – The data for a notebook.

notebook_response_data¶

class NotebookResponseData(*args, **kwargs)¶

Bases: ModelNormal

The data for a notebook.

Parameters:

attributes (NotebookResponseDataAttributes) – The attributes of a notebook.
id (int) – Unique notebook ID, assigned when you create the notebook.
type (NotebookResourceType) – Type of the Notebook resource.

notebook_response_data_attributes¶

class NotebookResponseDataAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attributes of a notebook.

Parameters:

author (NotebookAuthor, optional) – Attributes of user object returned by the API.
cells ([NotebookCellResponse]) – List of cells to display in the notebook.
created (datetime, optional) – UTC time stamp for when the notebook was created.
metadata (NotebookMetadata, optional) – Metadata associated with the notebook.
modified (datetime, optional) – UTC time stamp for when the notebook was last modified.
name (str) – The name of the notebook.
status (NotebookStatus, optional) – Publication status of the notebook. For now, always “published”.
time (NotebookGlobalTime) – Notebook global timeframe.

notebook_split_by¶

class NotebookSplitBy(*args, **kwargs)¶

Bases: ModelNormal

Object describing how to split the graph to display multiple visualizations per request.

Parameters:

keys ([str]) – Keys to split on.
tags ([str]) – Tags to split on.

notebook_status¶

class NotebookStatus(*args, **kwargs)¶

Bases: ModelSimple

Publication status of the notebook. For now, always “published”.

Parameters:

value (str) – If omitted defaults to “published”. Must be one of [“published”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

notebook_timeseries_cell_attributes¶

class NotebookTimeseriesCellAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attributes of a notebook timeseries cell.

Parameters:

definition (TimeseriesWidgetDefinition) – The timeseries visualization allows you to display the evolution of one or more metrics, log events, or Indexed Spans over time.
graph_size (NotebookGraphSize, optional) – The size of the graph.
split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.
time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

notebook_toplist_cell_attributes¶

class NotebookToplistCellAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attributes of a notebook toplist cell.

Parameters:

definition (ToplistWidgetDefinition) – The top list visualization enables you to display a list of Tag value like hostname or service with the most or least of any metric value, such as highest consumers of CPU, hosts with the least disk space, etc.
graph_size (NotebookGraphSize, optional) – The size of the graph.
split_by (NotebookSplitBy, optional) – Object describing how to split the graph to display multiple visualizations per request.
time (NotebookCellTime, none_type, optional) – Timeframe for the notebook cell. When ‘null’, the notebook global time is used.

notebook_update_cell¶

class NotebookUpdateCell(*args, **kwargs)¶

Bases: ModelComposed

Updating a notebook can either insert new cell(s) or update existing cell(s) by including the cell id. To delete existing cell(s), simply omit it from the list of cells.

Parameters:

attributes (NotebookCellCreateRequestAttributes) – The attributes of a notebook cell in create cell request. Valid cell types are markdown, timeseries, toplist, heatmap, distribution, log_stream. [More information on each graph visualization type.](https://docs.datadoghq.com/dashboards/widgets/)
type (NotebookCellResourceType) – Type of the Notebook Cell resource.
id (str) – Notebook cell ID.

notebook_update_data¶

class NotebookUpdateData(*args, **kwargs)¶

Bases: ModelNormal

The data for a notebook update request.

Parameters:

attributes (NotebookUpdateDataAttributes) – The data attributes of a notebook.
type (NotebookResourceType) – Type of the Notebook resource.

notebook_update_data_attributes¶

class NotebookUpdateDataAttributes(*args, **kwargs)¶

Bases: ModelNormal

The data attributes of a notebook.

Parameters:

cells ([NotebookUpdateCell]) – List of cells to display in the notebook.
metadata (NotebookMetadata, optional) – Metadata associated with the notebook.
name (str) – The name of the notebook.
status (NotebookStatus, optional) – Publication status of the notebook. For now, always “published”.
time (NotebookGlobalTime) – Notebook global timeframe.

notebook_update_request¶

class NotebookUpdateRequest(*args, **kwargs)¶

Bases: ModelNormal

The description of a notebook update request.

Parameters:: data (NotebookUpdateData) – The data for a notebook update request.

notebooks_response¶

class NotebooksResponse(*args, **kwargs)¶

Bases: ModelNormal

Notebooks get all response.

Parameters:

data ([NotebooksResponseData], optional) – List of notebook definitions.
meta (NotebooksResponseMeta, optional) – Searches metadata returned by the API.

notebooks_response_data¶

class NotebooksResponseData(*args, **kwargs)¶

Bases: ModelNormal

The data for a notebook in get all response.

Parameters:

attributes (NotebooksResponseDataAttributes) – The attributes of a notebook in get all response.
id (int) – Unique notebook ID, assigned when you create the notebook.
type (NotebookResourceType) – Type of the Notebook resource.

notebooks_response_data_attributes¶

class NotebooksResponseDataAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attributes of a notebook in get all response.

Parameters:

author (NotebookAuthor, optional) – Attributes of user object returned by the API.
cells ([NotebookCellResponse], optional) – List of cells to display in the notebook.
created (datetime, optional) – UTC time stamp for when the notebook was created.
metadata (NotebookMetadata, optional) – Metadata associated with the notebook.
modified (datetime, optional) – UTC time stamp for when the notebook was last modified.
name (str) – The name of the notebook.
status (NotebookStatus, optional) – Publication status of the notebook. For now, always “published”.
time (NotebookGlobalTime, optional) – Notebook global timeframe.

notebooks_response_meta¶

class NotebooksResponseMeta(*args, **kwargs)¶

Bases: ModelNormal

Searches metadata returned by the API.

Parameters:: page (NotebooksResponsePage, optional) – Pagination metadata returned by the API.

notebooks_response_page¶

class NotebooksResponsePage(*args, **kwargs)¶

Bases: ModelNormal

Pagination metadata returned by the API.

Parameters:

total_count (int, optional) – The total number of notebooks that would be returned if the request was not filtered by start and count parameters.
total_filtered_count (int, optional) – The total number of notebooks returned.

notify_end_state¶

class NotifyEndState(*args, **kwargs)¶

Bases: ModelSimple

A notification end state.

Parameters:

value (str) – Must be one of [“alert”, “no data”, “warn”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

notify_end_type¶

class NotifyEndType(*args, **kwargs)¶

Bases: ModelSimple

A notification end type.

Parameters:

value (str) – Must be one of [“canceled”, “expired”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

on_missing_data_option¶

class OnMissingDataOption(*args, **kwargs)¶

Bases: ModelSimple

Controls how groups or monitors are treated if an evaluation does not return any data points.: The default option results in different behavior depending on the monitor query type. For monitors using Count queries, an empty monitor evaluation is treated as 0 and is compared to the threshold conditions. For monitors using any query type other than Count, for example Gauge, Measure, or Rate, the monitor shows the last known status. This option is only available for APM Trace Analytics, Audit Trail, CI, Error Tracking, Event, Logs, and RUM monitors.

Parameters:

value (str) – Must be one of [“default”, “show_no_data”, “show_and_notify_no_data”, “resolve”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

org_downgraded_response¶

class OrgDowngradedResponse(*args, **kwargs)¶

Bases: ModelNormal

Status of downgrade

Parameters:: message (str, optional) – Information pertaining to the downgraded child organization.

organization¶

class Organization(*args, **kwargs)¶

Bases: ModelNormal

Create, edit, and manage organizations.

Parameters:

billing (OrganizationBilling, optional) – A JSON array of billing type. Deprecated.
created (str, optional) – Date of the organization creation.
description (str, optional) – Description of the organization.
name (str, optional) – The name of the child organization, limited to 32 characters.
public_id (str, optional) – The public_id of the organization you are operating within.
settings (OrganizationSettings, optional) – A JSON array of settings.
subscription (OrganizationSubscription, optional) – Subscription definition. Deprecated.
trial (bool, optional) – Only available for MSP customers. Allows child organizations to be created on a trial plan.

organization_billing¶

class OrganizationBilling(*args, **kwargs)¶

Bases: ModelNormal

A JSON array of billing type.

Parameters:: type (str, optional) – The type of billing. Only parent_billing is supported.

organization_create_body¶

class OrganizationCreateBody(*args, **kwargs)¶

Bases: ModelNormal

Object describing an organization to create.

Parameters:

billing (OrganizationBilling, optional) – A JSON array of billing type. Deprecated.
name (str) – The name of the new child-organization, limited to 32 characters.
subscription (OrganizationSubscription, optional) – Subscription definition. Deprecated.

organization_create_response¶

class OrganizationCreateResponse(*args, **kwargs)¶

Bases: ModelNormal

Response object for an organization creation.

Parameters:

api_key (ApiKey, optional) – Datadog API key.
application_key (ApplicationKey, optional) – An application key with its associated metadata.
org (Organization, optional) – Create, edit, and manage organizations.
user (User, optional) – Create, edit, and disable users.

organization_list_response¶

class OrganizationListResponse(*args, **kwargs)¶

Bases: ModelNormal

Response with the list of organizations.

Parameters:: orgs ([Organization], optional) – Array of organization objects.

organization_response¶

class OrganizationResponse(*args, **kwargs)¶

Bases: ModelNormal

Response with an organization.

Parameters:: org (Organization, optional) – Create, edit, and manage organizations.

organization_settings¶

class OrganizationSettings(*args, **kwargs)¶

Bases: ModelNormal

A JSON array of settings.

Parameters:

private_widget_share (bool, optional) – Whether or not the organization users can share widgets outside of Datadog.
saml (OrganizationSettingsSaml, optional) – Set the boolean property enabled to enable or disable single sign on with SAML. See the SAML documentation for more information about all SAML settings.
saml_autocreate_access_role (AccessRole, none_type, optional) – The access role of the user. Options are st (standard user), adm (admin user), or ro (read-only user).
saml_autocreate_users_domains (OrganizationSettingsSamlAutocreateUsersDomains, optional) – Has two properties, enabled (boolean) and domains , which is a list of domains without the @ symbol.
saml_can_be_enabled (bool, optional) – Whether or not SAML can be enabled for this organization.
saml_idp_endpoint (str, optional) – Identity provider endpoint for SAML authentication.
saml_idp_initiated_login (OrganizationSettingsSamlIdpInitiatedLogin, optional) – Has one property enabled (boolean).
saml_idp_metadata_uploaded (bool, optional) – Whether or not a SAML identity provider metadata file was provided to the Datadog organization.
saml_login_url (str, optional) – URL for SAML logging.
saml_strict_mode (OrganizationSettingsSamlStrictMode, optional) – Has one property enabled (boolean).

organization_settings_saml¶

class OrganizationSettingsSaml(*args, **kwargs)¶

Bases: ModelNormal

Set the boolean property enabled to enable or disable single sign on with SAML. See the SAML documentation for more information about all SAML settings.

Parameters:: enabled (bool, optional) – Whether or not SAML is enabled for this organization.

organization_settings_saml_autocreate_users_domains¶

class OrganizationSettingsSamlAutocreateUsersDomains(*args, **kwargs)¶

Bases: ModelNormal

Has two properties, enabled (boolean) and domains , which is a list of domains without the @ symbol.

Parameters:

domains ([str], optional) – List of domains where the SAML automated user creation is enabled.
enabled (bool, optional) – Whether or not the automated user creation based on SAML domain is enabled.

organization_settings_saml_idp_initiated_login¶

class OrganizationSettingsSamlIdpInitiatedLogin(*args, **kwargs)¶

Bases: ModelNormal

Has one property enabled (boolean).

Parameters:: enabled (bool, optional) – Whether SAML IdP initiated login is enabled, learn more in the SAML documentation.

organization_settings_saml_strict_mode¶

class OrganizationSettingsSamlStrictMode(*args, **kwargs)¶

Bases: ModelNormal

Has one property enabled (boolean).

Parameters:: enabled (bool, optional) – Whether or not the SAML strict mode is enabled. If true, all users must log in with SAML. Learn more on the SAML Strict documentation.

organization_subscription¶

class OrganizationSubscription(*args, **kwargs)¶

Bases: ModelNormal

Subscription definition.

Parameters:: type (str, optional) – The subscription type. Types available are trial , free , and pro.

pager_duty_service¶

class PagerDutyService(*args, **kwargs)¶

Bases: ModelNormal

The PagerDuty service that is available for integration with Datadog.

Parameters:

service_key (str) – Your service key in PagerDuty.
service_name (str) – Your service name associated with a service key in PagerDuty.

pager_duty_service_key¶

class PagerDutyServiceKey(*args, **kwargs)¶

Bases: ModelNormal

PagerDuty service object key.

Parameters:: service_key (str) – Your service key in PagerDuty.

pager_duty_service_name¶

class PagerDutyServiceName(*args, **kwargs)¶

Bases: ModelNormal

PagerDuty service object name.

Parameters:: service_name (str) – Your service name associated service key in PagerDuty.

pagination¶

class Pagination(*args, **kwargs)¶

Bases: ModelNormal

Pagination object.

Parameters:

total_count (int, optional) – Total count.
total_filtered_count (int, optional) – Total count of elements matched by the filter.

point¶

class Point(*args, **kwargs)¶

Bases: ModelSimple

Array of timeseries points.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

powerpack_template_variable_contents¶

class PowerpackTemplateVariableContents(*args, **kwargs)¶

Bases: ModelNormal

Powerpack template variable contents.

Parameters:

name (str) – The name of the variable.
prefix (str, optional) – The tag prefix associated with the variable.
values ([str]) – One or many template variable values within the saved view, which will be unioned together using OR if more than one is specified.

powerpack_template_variables¶

class PowerpackTemplateVariables(*args, **kwargs)¶

Bases: ModelNormal

Powerpack template variables.

Parameters:

controlled_by_powerpack ([PowerpackTemplateVariableContents], optional) – Template variables controlled at the powerpack level.
controlled_externally ([PowerpackTemplateVariableContents], optional) – Template variables controlled by the external resource, such as the dashboard this powerpack is on.

powerpack_widget_definition¶

class PowerpackWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The powerpack widget allows you to keep similar graphs together on your timeboard. Each group has a custom header, can hold one to many graphs, and is collapsible.

Parameters:

background_color (str, optional) – Background color of the powerpack title.
banner_img (str, optional) – URL of image to display as a banner for the powerpack.
powerpack_id (str) – UUID of the associated powerpack.
show_title (bool, optional) – Whether to show the title or not.
template_variables (PowerpackTemplateVariables, optional) – Powerpack template variables.
title (str, optional) – Title of the widget.
type (PowerpackWidgetDefinitionType) – Type of the powerpack widget.

powerpack_widget_definition_type¶

class PowerpackWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the powerpack widget.

Parameters:

value (str) – If omitted defaults to “powerpack”. Must be one of [“powerpack”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

process_query_definition¶

class ProcessQueryDefinition(*args, **kwargs)¶

Bases: ModelNormal

The process query to use in the widget.

Parameters:

filter_by ([str], optional) – List of processes.
limit (int, optional) – Max number of items in the filter list.
metric (str) – Your chosen metric.
search_by (str, optional) – Your chosen search term.

query_sort_order¶

class QuerySortOrder(*args, **kwargs)¶

Bases: ModelSimple

Direction of sort.

Parameters:

value (str) – If omitted defaults to “desc”. Must be one of [“asc”, “desc”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

query_value_widget_definition¶

class QueryValueWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

Query values display the current value of a given metric, APM, or log query.

Parameters:

autoscale (bool, optional) – Whether to use auto-scaling or not.
custom_links ([WidgetCustomLink], optional) – List of custom links.
custom_unit (str, optional) – Display a unit of your choice on the widget.
precision (int, optional) – Number of decimals to show. If not defined, the widget uses the raw value.
requests ([QueryValueWidgetRequest]) – Widget definition.
text_align (WidgetTextAlign, optional) – How to align the text on the widget.
time (WidgetTime, optional) – Time setting for the widget.
timeseries_background (TimeseriesBackground, optional) – Set a timeseries on the widget background.
title (str, optional) – Title of your widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (QueryValueWidgetDefinitionType) – Type of the query value widget.

query_value_widget_definition_type¶

class QueryValueWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the query value widget.

Parameters:

value (str) – If omitted defaults to “query_value”. Must be one of [“query_value”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

query_value_widget_request¶

class QueryValueWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated query value widget.

Parameters:

aggregator (WidgetAggregator, optional) – Aggregator used for the request.
apm_query (LogQueryDefinition, optional) – The log query.
audit_query (LogQueryDefinition, optional) – The log query.
conditional_formats ([WidgetConditionalFormat], optional) – List of conditional formats.
event_query (LogQueryDefinition, optional) – The log query.
formulas ([WidgetFormula], optional) – List of formulas that operate on queries.
log_query (LogQueryDefinition, optional) – The log query.
network_query (LogQueryDefinition, optional) – The log query.
process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.
profile_metrics_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – TODO.
queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.
response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.

reference_table_logs_lookup_processor¶

class ReferenceTableLogsLookupProcessor(*args, **kwargs)¶

Bases: ModelNormal

Note : Reference Tables are in public beta. Use the Lookup Processor to define a mapping between a log attribute and a human readable value saved in a Reference Table. For example, you can use the Lookup Processor to map an internal service ID into a human readable service name. Alternatively, you could also use it to check if the MAC address that just attempted to connect to the production environment belongs to your list of stolen machines.

Parameters:

is_enabled (bool, optional) – Whether or not the processor is enabled.
lookup_enrichment_table (str) – Name of the Reference Table for the source attribute and their associated target attribute values.
name (str, optional) – Name of the processor.
source (str) – Source attribute used to perform the lookup.
target (str) – Name of the attribute that contains the corresponding value in the mapping list.
type (LogsLookupProcessorType) – Type of logs lookup processor.

response_meta_attributes¶

class ResponseMetaAttributes(*args, **kwargs)¶

Bases: ModelNormal

Object describing meta attributes of response.

Parameters:: page (Pagination, optional) – Pagination object.

run_workflow_widget_definition¶

class RunWorkflowWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

Run workflow is widget that allows you to run a workflow from a dashboard.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
inputs ([RunWorkflowWidgetInput], optional) – Array of workflow inputs to map to dashboard template variables.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of your widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (RunWorkflowWidgetDefinitionType) – Type of the run workflow widget.
workflow_id (str) – Workflow id.

run_workflow_widget_definition_type¶

class RunWorkflowWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the run workflow widget.

Parameters:

value (str) – If omitted defaults to “run_workflow”. Must be one of [“run_workflow”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

run_workflow_widget_input¶

class RunWorkflowWidgetInput(*args, **kwargs)¶

Bases: ModelNormal

Object to map a dashboard template variable to a workflow input.

Parameters:

name (str) – Name of the workflow input.
value (str) – Dashboard template variable. Can be suffixed with ‘.value’ or ‘.key’.

scatter_plot_request¶

class ScatterPlotRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated scatter plot.

Parameters:

aggregator (ScatterplotWidgetAggregator, optional) – Aggregator used for the request.
apm_query (LogQueryDefinition, optional) – The log query.
event_query (LogQueryDefinition, optional) – The log query.
log_query (LogQueryDefinition, optional) – The log query.
network_query (LogQueryDefinition, optional) – The log query.
process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.
profile_metrics_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – Query definition.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.

scatter_plot_widget_definition¶

class ScatterPlotWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The scatter plot visualization allows you to graph a chosen scope over two different metrics with their respective aggregation.

Parameters:

color_by_groups ([str], optional) – List of groups used for colors.
custom_links ([WidgetCustomLink], optional) – List of custom links.
requests (ScatterPlotWidgetDefinitionRequests) – Widget definition.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of your widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (ScatterPlotWidgetDefinitionType) – Type of the scatter plot widget.
xaxis (WidgetAxis, optional) – Axis controls for the widget.
yaxis (WidgetAxis, optional) – Axis controls for the widget.

scatter_plot_widget_definition_requests¶

class ScatterPlotWidgetDefinitionRequests(*args, **kwargs)¶

Bases: ModelNormal

Widget definition.

Parameters:

table (ScatterplotTableRequest, optional) – Scatterplot request containing formulas and functions.
x (ScatterPlotRequest, optional) – Updated scatter plot.
y (ScatterPlotRequest, optional) – Updated scatter plot.

scatter_plot_widget_definition_type¶

class ScatterPlotWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the scatter plot widget.

Parameters:

value (str) – If omitted defaults to “scatterplot”. Must be one of [“scatterplot”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

scatterplot_dimension¶

class ScatterplotDimension(*args, **kwargs)¶

Bases: ModelSimple

Dimension of the Scatterplot.

Parameters:

value (str) – Must be one of [“x”, “y”, “radius”, “color”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

scatterplot_table_request¶

class ScatterplotTableRequest(*args, **kwargs)¶

Bases: ModelNormal

Scatterplot request containing formulas and functions.

Parameters:

formulas ([ScatterplotWidgetFormula], optional) – List of Scatterplot formulas that operate on queries.
queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.
response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

scatterplot_widget_aggregator¶

class ScatterplotWidgetAggregator(*args, **kwargs)¶

Bases: ModelSimple

Aggregator used for the request.

Parameters:

value (str) – Must be one of [“avg”, “last”, “max”, “min”, “sum”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

scatterplot_widget_formula¶

class ScatterplotWidgetFormula(*args, **kwargs)¶

Bases: ModelNormal

Formula to be used in a Scatterplot widget query.

Parameters:

alias (str, optional) – Expression alias.
dimension (ScatterplotDimension) – Dimension of the Scatterplot.
formula (str) – String expression built from queries, formulas, and functions.

search_service_level_objective¶

class SearchServiceLevelObjective(*args, **kwargs)¶

Bases: ModelNormal

A service level objective data container.

Parameters:: data (SearchServiceLevelObjectiveData, optional) – A service level objective ID and attributes.

search_service_level_objective_attributes¶

class SearchServiceLevelObjectiveAttributes(*args, **kwargs)¶

Bases: ModelNormal

A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , and tags ).

Parameters:

all_tags ([str], optional) – A list of tags associated with this service level objective. Always included in service level objective responses (but may be empty).
created_at (int, optional) –
Creation timestamp (UNIX time in seconds)

Always included in service level objective responses.
creator (SLOCreator, none_type, optional) – The creator of the SLO
description (str, none_type, optional) –
A user-defined description of the service level objective.

Always included in service level objective responses (but may be null ). Optional in create/update requests.
env_tags ([str], optional) – Tags with the env tag key.
groups ([str], none_type, optional) – A list of (up to 100) monitor groups that narrow the scope of a monitor service level objective. Included in service level objective responses if it is not empty.
modified_at (int, optional) –
Modification timestamp (UNIX time in seconds)

Always included in service level objective responses.
monitor_ids ([int], none_type, optional) – A list of monitor ids that defines the scope of a monitor service level objective.
name (str, optional) – The name of the service level objective object.
overall_status ([SLOOverallStatuses], optional) – calculated status and error budget remaining.
query (SearchSLOQuery, none_type, optional) – A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.
service_tags ([str], optional) – Tags with the service tag key.
slo_type (SLOType, optional) – The type of the service level objective.
status (SLOStatus, optional) – Status of the SLO’s primary timeframe.
team_tags ([str], optional) – Tags with the team tag key.
thresholds ([SearchSLOThreshold], optional) – The thresholds (timeframes and associated targets) for this service level objective object.

search_service_level_objective_data¶

class SearchServiceLevelObjectiveData(*args, **kwargs)¶

Bases: ModelNormal

A service level objective ID and attributes.

Parameters:

attributes (SearchServiceLevelObjectiveAttributes, optional) – A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , and tags ).
id (str, optional) –
A unique identifier for the service level objective object.

Always included in service level objective responses.
type (str, optional) – The type of the object, must be slo.

search_slo_query¶

class SearchSLOQuery(*args, **kwargs)¶

Bases: ModelNormal

A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.

Parameters:

denominator (str, optional) – A Datadog metric query for total (valid) events.
metrics ([str], none_type, optional) – Metric names used in the query’s numerator and denominator. This field will return null and will be implemented in the next version of this endpoint.
numerator (str, optional) – A Datadog metric query for good events.

search_slo_response¶

class SearchSLOResponse(*args, **kwargs)¶

Bases: ModelNormal

A search SLO response containing results from the search query.

Parameters:

data (SearchSLOResponseData, optional) – Data from search SLO response.
links (SearchSLOResponseLinks, optional) – Pagination links.
meta (SearchSLOResponseMeta, optional) – Searches metadata returned by the API.

search_slo_response_data¶

class SearchSLOResponseData(*args, **kwargs)¶

Bases: ModelNormal

Data from search SLO response.

Parameters:

attributes (SearchSLOResponseDataAttributes, optional) – Attributes
type (str, optional) – Type of service level objective result.

search_slo_response_data_attributes¶

class SearchSLOResponseDataAttributes(*args, **kwargs)¶

Bases: ModelNormal

Attributes

Parameters:

facets (SearchSLOResponseDataAttributesFacets, optional) – Facets
slos ([SearchServiceLevelObjective], optional) – SLOs

search_slo_response_data_attributes_facets¶

class SearchSLOResponseDataAttributesFacets(*args, **kwargs)¶

Bases: ModelNormal

Facets

Parameters:

all_tags ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – All tags associated with an SLO.
creator_name ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – Creator of an SLO.
env_tags ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – Tags with the env tag key.
service_tags ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – Tags with the service tag key.
slo_type ([SearchSLOResponseDataAttributesFacetsObjectInt], optional) – Type of SLO.
target ([SearchSLOResponseDataAttributesFacetsObjectInt], optional) – SLO Target
team_tags ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – Tags with the team tag key.
timeframe ([SearchSLOResponseDataAttributesFacetsObjectString], optional) – Timeframes of SLOs.

search_slo_response_data_attributes_facets_object_int¶

class SearchSLOResponseDataAttributesFacetsObjectInt(*args, **kwargs)¶

Bases: ModelNormal

Facet

Parameters:

count (int, optional) – Count
name (float, optional) – Facet

search_slo_response_data_attributes_facets_object_string¶

class SearchSLOResponseDataAttributesFacetsObjectString(*args, **kwargs)¶

Bases: ModelNormal

Facet

Parameters:

count (int, optional) – Count
name (str, optional) – Facet

search_slo_response_links¶

class SearchSLOResponseLinks(*args, **kwargs)¶

Bases: ModelNormal

Pagination links.

Parameters:

first (str, optional) – Link to last page.
last (str, none_type, optional) – Link to first page.
next (str, optional) – Link to the next page.
prev (str, none_type, optional) – Link to previous page.
self (str, optional) – Link to current page.

search_slo_response_meta¶

class SearchSLOResponseMeta(*args, **kwargs)¶

Bases: ModelNormal

Searches metadata returned by the API.

Parameters:: pagination (SearchSLOResponseMetaPage, optional) – Pagination metadata returned by the API.

search_slo_response_meta_page¶

class SearchSLOResponseMetaPage(*args, **kwargs)¶

Bases: ModelNormal

Pagination metadata returned by the API.

Parameters:

first_number (int, optional) – The first number.
last_number (int, optional) – The last number.
next_number (int, optional) – The next number.
number (int, optional) – The page number.
prev_number (int, optional) – The previous page number.
size (int, optional) – The size of the response.
total (int, optional) – The total number of SLOs in the response.
type (str, optional) – Type of pagination.

search_slo_threshold¶

class SearchSLOThreshold(*args, **kwargs)¶

Bases: ModelNormal

SLO thresholds (target and optionally warning) for a single time window.

Parameters:

target (float) – The target value for the service level indicator within the corresponding timeframe.
target_display (str, optional) –
A string representation of the target that indicates its precision. It uses trailing zeros to show significant decimal places (for example 98.00 ).

Always included in service level objective responses. Ignored in create/update requests.
timeframe (SearchSLOTimeframe) – The SLO time window options.
warning (float, none_type, optional) – The warning value for the service level objective.
warning_display (str, none_type, optional) –
A string representation of the warning target (see the description of the target_display field for details).

Included in service level objective responses if a warning target exists. Ignored in create/update requests.

search_slo_timeframe¶

class SearchSLOTimeframe(*args, **kwargs)¶

Bases: ModelSimple

The SLO time window options.

Parameters:

value (str) – Must be one of [“7d”, “30d”, “90d”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

selectable_template_variable_items¶

class SelectableTemplateVariableItems(*args, **kwargs)¶

Bases: ModelNormal

Object containing the template variable’s name, associated tag/attribute, default value and selectable values.

Parameters:

default_value (str, optional) – The default value of the template variable.
name (str, optional) – Name of the template variable.
prefix (str, optional) – The tag/attribute key associated with the template variable.
visible_tags ([str], none_type, optional) – List of visible tag values on the shared dashboard.

series¶

class Series(*args, **kwargs)¶

Bases: ModelNormal

A metric to submit to Datadog. See Datadog metrics.

Parameters:

host (str, optional) – The name of the host that produced the metric.
interval (int, none_type, optional) – If the type of the metric is rate or count, define the corresponding interval.
metric (str) – The name of the timeseries.
points ([Point]) – Points relating to a metric. All points must be tuples with timestamp and a scalar value (cannot be a string). Timestamps should be in POSIX time in seconds, and cannot be more than ten minutes in the future or more than one hour in the past.
tags ([str], optional) – A list of tags associated with the metric.
type (str, optional) – The type of the metric. Valid types are “”, count , gauge , and rate.

service_check¶

class ServiceCheck(*args, **kwargs)¶

Bases: ModelNormal

An object containing service check and status.

Parameters:

check (str) – The check.
host_name (str) – The host name correlated with the check.
message (str, optional) – Message containing check status.
status (ServiceCheckStatus) – The status of a service check. Set to 0 for OK, 1 for warning, 2 for critical, and 3 for unknown.
tags ([str]) – Tags related to a check.
timestamp (int, optional) – Time of check.

service_check_status¶

class ServiceCheckStatus(*args, **kwargs)¶

Bases: ModelSimple

The status of a service check. Set to 0 for OK, 1 for warning, 2 for critical, and 3 for unknown.

Parameters:

value (int) – Must be one of [0, 1, 2, 3].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

service_checks¶

class ServiceChecks(*args, **kwargs)¶

Bases: ModelSimple

The service checks.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

service_level_objective¶

class ServiceLevelObjective(*args, **kwargs)¶

Bases: ModelNormal

A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , tags , etc.).

Parameters:

created_at (int, optional) –
Creation timestamp (UNIX time in seconds)

Always included in service level objective responses.
creator (Creator, optional) – Object describing the creator of the shared element.
description (str, none_type, optional) –
A user-defined description of the service level objective.

Always included in service level objective responses (but may be null ). Optional in create/update requests.
groups ([str], optional) –
A list of (up to 100) monitor groups that narrow the scope of a monitor service level objective.

Included in service level objective responses if it is not empty. Optional in create/update requests for monitor service level objectives, but may only be used when then length of the monitor_ids field is one.
id (str, optional) –
A unique identifier for the service level objective object.

Always included in service level objective responses.
modified_at (int, optional) –
Modification timestamp (UNIX time in seconds)

Always included in service level objective responses.
monitor_ids ([int], optional) – A list of monitor ids that defines the scope of a monitor service level objective. Required if type is monitor.
monitor_tags ([str], optional) – The union of monitor tags for all monitors referenced by the monitor_ids field. Always included in service level objective responses for monitor-based service level objectives (but may be empty). Ignored in create/update requests. Does not affect which monitors are included in the service level objective (that is determined entirely by the monitor_ids field).
name (str) – The name of the service level objective object.
query (ServiceLevelObjectiveQuery, optional) – A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.
sli_specification (SLOSliSpec, optional) – A generic SLI specification. This is currently used for time-slice SLOs only.
tags ([str], optional) – A list of tags associated with this service level objective. Always included in service level objective responses (but may be empty). Optional in create/update requests.
target_threshold (float, optional) – The target threshold such that when the service level indicator is above this threshold over the given timeframe, the objective is being met.
thresholds ([SLOThreshold]) – The thresholds (timeframes and associated targets) for this service level objective object.
timeframe (SLOTimeframe, optional) – The SLO time window options.
type (SLOType) – The type of the service level objective.
warning_threshold (float, optional) – The optional warning threshold such that when the service level indicator is below this value for the given threshold, but above the target threshold, the objective appears in a “warning” state. This value must be greater than the target threshold.

service_level_objective_query¶

class ServiceLevelObjectiveQuery(*args, **kwargs)¶

Bases: ModelNormal

A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.

Parameters:

denominator (str) – A Datadog metric query for total (valid) events.
numerator (str) – A Datadog metric query for good events.

service_level_objective_request¶

class ServiceLevelObjectiveRequest(*args, **kwargs)¶

Bases: ModelNormal

A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , tags , etc.).

Parameters:

description (str, none_type, optional) –
A user-defined description of the service level objective.

Always included in service level objective responses (but may be null ). Optional in create/update requests.
groups ([str], optional) –
A list of (up to 100) monitor groups that narrow the scope of a monitor service level objective.

Included in service level objective responses if it is not empty. Optional in create/update requests for monitor service level objectives, but may only be used when then length of the monitor_ids field is one.
monitor_ids ([int], optional) – A list of monitor IDs that defines the scope of a monitor service level objective. Required if type is monitor.
name (str) – The name of the service level objective object.
query (ServiceLevelObjectiveQuery, optional) – A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.
sli_specification (SLOSliSpec, optional) – A generic SLI specification. This is currently used for time-slice SLOs only.
tags ([str], optional) – A list of tags associated with this service level objective. Always included in service level objective responses (but may be empty). Optional in create/update requests.
target_threshold (float, optional) – The target threshold such that when the service level indicator is above this threshold over the given timeframe, the objective is being met.
thresholds ([SLOThreshold]) – The thresholds (timeframes and associated targets) for this service level objective object.
timeframe (SLOTimeframe, optional) – The SLO time window options.
type (SLOType) – The type of the service level objective.
warning_threshold (float, optional) – The optional warning threshold such that when the service level indicator is below this value for the given threshold, but above the target threshold, the objective appears in a “warning” state. This value must be greater than the target threshold.

service_map_widget_definition¶

class ServiceMapWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

This widget displays a map of a service to all of the services that call it, and all of the services that it calls.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
filters ([str]) – Your environment and primary tag (or * if enabled for your account).
service (str) – The ID of the service you want to map.
title (str, optional) – The title of your widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (ServiceMapWidgetDefinitionType) – Type of the service map widget.

service_map_widget_definition_type¶

class ServiceMapWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the service map widget.

Parameters:

value (str) – If omitted defaults to “servicemap”. Must be one of [“servicemap”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

service_summary_widget_definition¶

class ServiceSummaryWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The service summary displays the graphs of a chosen service in your screenboard. Only available on FREE layout dashboards.

Parameters:

display_format (WidgetServiceSummaryDisplayFormat, optional) – Number of columns to display.
env (str) – APM environment.
service (str) – APM service.
show_breakdown (bool, optional) – Whether to show the latency breakdown or not.
show_distribution (bool, optional) – Whether to show the latency distribution or not.
show_errors (bool, optional) – Whether to show the error metrics or not.
show_hits (bool, optional) – Whether to show the hits metrics or not.
show_latency (bool, optional) – Whether to show the latency metrics or not.
show_resource_list (bool, optional) – Whether to show the resource list or not.
size_format (WidgetSizeFormat, optional) – Size of the widget.
span_name (str) – APM span name.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (ServiceSummaryWidgetDefinitionType) – Type of the service summary widget.

service_summary_widget_definition_type¶

class ServiceSummaryWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the service summary widget.

Parameters:

value (str) – If omitted defaults to “trace_service”. Must be one of [“trace_service”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

shared_dashboard¶

class SharedDashboard(*args, **kwargs)¶

Bases: ModelNormal

The metadata object associated with how a dashboard has been/will be shared.

Parameters:

author (SharedDashboardAuthor, optional) – User who shared the dashboard.
created_at (datetime, optional) – Date the dashboard was shared.
dashboard_id (str) – ID of the dashboard to share.
dashboard_type (DashboardType) – The type of the associated private dashboard.
global_time (DashboardGlobalTime, optional) – Object containing the live span selection for the dashboard.
global_time_selectable_enabled (bool, none_type, optional) – Whether to allow viewers to select a different global time setting for the shared dashboard.
public_url (str, optional) – URL of the shared dashboard.
selectable_template_vars ([SelectableTemplateVariableItems], none_type, optional) – List of objects representing template variables on the shared dashboard which can have selectable values.
share_list ([str], none_type, optional) – List of email addresses that can receive an invitation to access to the shared dashboard.
share_type (DashboardShareType, none_type, optional) – Type of sharing access (either open to anyone who has the public URL or invite-only).
token (str, optional) – A unique token assigned to the shared dashboard.

shared_dashboard_author¶

class SharedDashboardAuthor(*args, **kwargs)¶

Bases: ModelNormal

User who shared the dashboard.

Parameters:

handle (str, optional) – Identifier of the user who shared the dashboard.
name (str, none_type, optional) – Name of the user who shared the dashboard.

shared_dashboard_invites¶

class SharedDashboardInvites(*args, **kwargs)¶

Bases: ModelNormal

Invitations data and metadata that exists for a shared dashboard returned by the API.

Parameters:

data (SharedDashboardInvitesData) – An object or list of objects containing the information for an invitation to a shared dashboard.
meta (SharedDashboardInvitesMeta, optional) – Pagination metadata returned by the API.

shared_dashboard_invites_data¶

class SharedDashboardInvitesData(*args, **kwargs)¶

Bases: ModelComposed

An object or list of objects containing the information for an invitation to a shared dashboard.

Parameters:

attributes (SharedDashboardInvitesDataObjectAttributes) – Attributes of the shared dashboard invitation
type (DashboardInviteType) – Type for shared dashboard invitation request body.

shared_dashboard_invites_data_list¶

class SharedDashboardInvitesDataList(*args, **kwargs)¶

Bases: ModelSimple

A list of objects containing the information for an invitation(s) to a shared dashboard.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

shared_dashboard_invites_data_object¶

class SharedDashboardInvitesDataObject(*args, **kwargs)¶

Bases: ModelNormal

Object containing the information for an invitation to a shared dashboard.

Parameters:

attributes (SharedDashboardInvitesDataObjectAttributes) – Attributes of the shared dashboard invitation
type (DashboardInviteType) – Type for shared dashboard invitation request body.

shared_dashboard_invites_data_object_attributes¶

class SharedDashboardInvitesDataObjectAttributes(*args, **kwargs)¶

Bases: ModelNormal

Attributes of the shared dashboard invitation

Parameters:

created_at (datetime, optional) – When the invitation was sent.
email (str, optional) – An email address that an invitation has been (or if used in invitation request, will be) sent to.
has_session (bool, optional) – Indicates whether an active session exists for the invitation (produced when a user clicks the link in the email).
invitation_expiry (datetime, optional) – When the invitation expires.
session_expiry (datetime, none_type, optional) – When the invited user’s session expires. null if the invitation has no associated session.
share_token (str, optional) – The unique token of the shared dashboard that was (or is to be) shared.

shared_dashboard_invites_meta¶

class SharedDashboardInvitesMeta(*args, **kwargs)¶

Bases: ModelNormal

Pagination metadata returned by the API.

Parameters:: page (SharedDashboardInvitesMetaPage, optional) – Object containing the total count of invitations across all pages

shared_dashboard_invites_meta_page¶

class SharedDashboardInvitesMetaPage(*args, **kwargs)¶

Bases: ModelNormal

Object containing the total count of invitations across all pages

Parameters:: total_count (int, optional) – The total number of invitations on this shared board, across all pages.

shared_dashboard_update_request¶

class SharedDashboardUpdateRequest(*args, **kwargs)¶

Bases: ModelNormal

Update a shared dashboard’s settings.

Parameters:

global_time (SharedDashboardUpdateRequestGlobalTime, none_type) – Timeframe setting for the shared dashboard.
global_time_selectable_enabled (bool, none_type, optional) – Whether to allow viewers to select a different global time setting for the shared dashboard.
selectable_template_vars ([SelectableTemplateVariableItems], none_type, optional) – List of objects representing template variables on the shared dashboard which can have selectable values.
share_list ([str], none_type, optional) – List of email addresses that can be given access to the shared dashboard.
share_type (DashboardShareType, none_type, optional) – Type of sharing access (either open to anyone who has the public URL or invite-only).

shared_dashboard_update_request_global_time¶

class SharedDashboardUpdateRequestGlobalTime(*args, **kwargs)¶

Bases: ModelNormal

Timeframe setting for the shared dashboard.

Parameters:: live_span (DashboardGlobalTimeLiveSpan, optional) – Dashboard global time live_span selection

signal_archive_reason¶

class SignalArchiveReason(*args, **kwargs)¶

Bases: ModelSimple

Reason why a signal has been archived.

Parameters:

value (str) – Must be one of [“none”, “false_positive”, “testing_or_maintenance”, “investigated_case_opened”, “other”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

signal_assignee_update_request¶

class SignalAssigneeUpdateRequest(*args, **kwargs)¶

Bases: ModelNormal

Attributes describing an assignee update operation over a security signal.

Parameters:

assignee (str) – The UUID of the user being assigned. Use empty string to return signal to unassigned.
version (int, optional) – Version of the updated signal. If server side version is higher, update will be rejected.

signal_state_update_request¶

class SignalStateUpdateRequest(*args, **kwargs)¶

Bases: ModelNormal

Attributes describing the change of state for a given state.

Parameters:

archive_comment (str, optional) – Optional comment to explain why a signal is being archived.
archive_reason (SignalArchiveReason, optional) – Reason why a signal has been archived.
state (SignalTriageState) – The new triage state of the signal.
version (int, optional) – Version of the updated signal. If server side version is higher, update will be rejected.

signal_triage_state¶

class SignalTriageState(*args, **kwargs)¶

Bases: ModelSimple

The new triage state of the signal.

Parameters:

value (str) – Must be one of [“open”, “archived”, “under_review”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slack_integration_channel¶

class SlackIntegrationChannel(*args, **kwargs)¶

Bases: ModelNormal

The Slack channel configuration.

Parameters:

display (SlackIntegrationChannelDisplay, optional) – Configuration options for what is shown in an alert event message.
name (str, optional) – Your channel name.

slack_integration_channel_display¶

class SlackIntegrationChannelDisplay(*args, **kwargs)¶

Bases: ModelNormal

Configuration options for what is shown in an alert event message.

Parameters:

message (bool, optional) – Show the main body of the alert event.
notified (bool, optional) – Show the list of @-handles in the alert event.
snapshot (bool, optional) – Show the alert event’s snapshot image.
tags (bool, optional) – Show the scopes on which the monitor alerted.

slack_integration_channels¶

class SlackIntegrationChannels(*args, **kwargs)¶

Bases: ModelSimple

A list of configured Slack channels.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_bulk_delete¶

class SLOBulkDelete(*args, **kwargs)¶

Bases: ModelNormal

A map of service level objective object IDs to arrays of timeframes, which indicate the thresholds to delete for each ID.

slo_bulk_delete_error¶

class SLOBulkDeleteError(*args, **kwargs)¶

Bases: ModelNormal

Object describing the error.

Parameters:

id (str) – The ID of the service level objective object associated with this error.
message (str) – The error message.
timeframe (SLOErrorTimeframe) – The timeframe of the threshold associated with this error or “all” if all thresholds are affected.

slo_bulk_delete_response¶

class SLOBulkDeleteResponse(*args, **kwargs)¶

Bases: ModelNormal

The bulk partial delete service level objective object endpoint response.

This endpoint operates on multiple service level objective objects, so it may be partially successful. In such cases, the “data” and “error” fields in this response indicate which deletions succeeded and failed.

Parameters:

data (SLOBulkDeleteResponseData, optional) – An array of service level objective objects.
errors ([SLOBulkDeleteError], optional) – Array of errors object returned.

slo_bulk_delete_response_data¶

class SLOBulkDeleteResponseData(*args, **kwargs)¶

Bases: ModelNormal

An array of service level objective objects.

Parameters:

deleted ([str], optional) – An array of service level objective object IDs that indicates which objects that were completely deleted.
updated ([str], optional) – An array of service level objective object IDs that indicates which objects that were modified (objects for which at least one threshold was deleted, but that were not completely deleted).

slo_correction¶

class SLOCorrection(*args, **kwargs)¶

Bases: ModelNormal

The response object of a list of SLO corrections.

Parameters:

attributes (SLOCorrectionResponseAttributes, optional) – The attribute object associated with the SLO correction.
id (str, optional) – The ID of the SLO correction.
type (SLOCorrectionType, optional) – SLO correction resource type.

slo_correction_category¶

class SLOCorrectionCategory(*args, **kwargs)¶

Bases: ModelSimple

Category the SLO correction belongs to.

Parameters:

value (str) – Must be one of [“Scheduled Maintenance”, “Outside Business Hours”, “Deployment”, “Other”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_correction_create_data¶

class SLOCorrectionCreateData(*args, **kwargs)¶

Bases: ModelNormal

The data object associated with the SLO correction to be created.

Parameters:

attributes (SLOCorrectionCreateRequestAttributes, optional) – The attribute object associated with the SLO correction to be created.
type (SLOCorrectionType) – SLO correction resource type.

slo_correction_create_request¶

class SLOCorrectionCreateRequest(*args, **kwargs)¶

Bases: ModelNormal

An object that defines a correction to be applied to an SLO.

Parameters:: data (SLOCorrectionCreateData, optional) – The data object associated with the SLO correction to be created.

slo_correction_create_request_attributes¶

class SLOCorrectionCreateRequestAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attribute object associated with the SLO correction to be created.

Parameters:

category (SLOCorrectionCategory) – Category the SLO correction belongs to.
description (str, optional) – Description of the correction being made.
duration (int, optional) – Length of time (in seconds) for a specified rrule recurring SLO correction.
end (int, optional) – Ending time of the correction in epoch seconds.
rrule (str, optional) – The recurrence rules as defined in the iCalendar RFC 5545. The supported rules for SLO corrections are FREQ , INTERVAL , COUNT , UNTIL and BYDAY.
slo_id (str) – ID of the SLO that this correction applies to.
start (int) – Starting time of the correction in epoch seconds.
timezone (str, optional) – The timezone to display in the UI for the correction times (defaults to “UTC”).

slo_correction_list_response¶

class SLOCorrectionListResponse(*args, **kwargs)¶

Bases: ModelNormal

A list of SLO correction objects.

Parameters:

data ([SLOCorrection], optional) – The list of of SLO corrections objects.
meta (ResponseMetaAttributes, optional) – Object describing meta attributes of response.

slo_correction_response¶

class SLOCorrectionResponse(*args, **kwargs)¶

Bases: ModelNormal

The response object of an SLO correction.

Parameters:: data (SLOCorrection, optional) – The response object of a list of SLO corrections.

slo_correction_response_attributes¶

class SLOCorrectionResponseAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attribute object associated with the SLO correction.

Parameters:

category (SLOCorrectionCategory, optional) – Category the SLO correction belongs to.
created_at (int, none_type, optional) – The epoch timestamp of when the correction was created at.
creator (Creator, optional) – Object describing the creator of the shared element.
description (str, optional) – Description of the correction being made.
duration (int, none_type, optional) – Length of time (in seconds) for a specified rrule recurring SLO correction.
end (int, none_type, optional) – Ending time of the correction in epoch seconds.
modified_at (int, none_type, optional) – The epoch timestamp of when the correction was modified at.
modifier (SLOCorrectionResponseAttributesModifier, none_type, optional) – Modifier of the object.
rrule (str, none_type, optional) – The recurrence rules as defined in the iCalendar RFC 5545. The supported rules for SLO corrections are FREQ , INTERVAL , COUNT , UNTIL and BYDAY.
slo_id (str, optional) – ID of the SLO that this correction applies to.
start (int, optional) – Starting time of the correction in epoch seconds.
timezone (str, optional) – The timezone to display in the UI for the correction times (defaults to “UTC”).

slo_correction_response_attributes_modifier¶

class SLOCorrectionResponseAttributesModifier(*args, **kwargs)¶

Bases: ModelNormal

Modifier of the object.

Parameters:

email (str, optional) – Email of the Modifier.
handle (str, optional) – Handle of the Modifier.
name (str, optional) – Name of the Modifier.

slo_correction_type¶

class SLOCorrectionType(*args, **kwargs)¶

Bases: ModelSimple

SLO correction resource type.

Parameters:

value (str) – If omitted defaults to “correction”. Must be one of [“correction”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_correction_update_data¶

class SLOCorrectionUpdateData(*args, **kwargs)¶

Bases: ModelNormal

The data object associated with the SLO correction to be updated.

Parameters:

attributes (SLOCorrectionUpdateRequestAttributes, optional) – The attribute object associated with the SLO correction to be updated.
type (SLOCorrectionType, optional) – SLO correction resource type.

slo_correction_update_request¶

class SLOCorrectionUpdateRequest(*args, **kwargs)¶

Bases: ModelNormal

An object that defines a correction to be applied to an SLO.

Parameters:: data (SLOCorrectionUpdateData, optional) – The data object associated with the SLO correction to be updated.

slo_correction_update_request_attributes¶

class SLOCorrectionUpdateRequestAttributes(*args, **kwargs)¶

Bases: ModelNormal

The attribute object associated with the SLO correction to be updated.

Parameters:

category (SLOCorrectionCategory, optional) – Category the SLO correction belongs to.
description (str, optional) – Description of the correction being made.
duration (int, optional) – Length of time (in seconds) for a specified rrule recurring SLO correction.
end (int, optional) – Ending time of the correction in epoch seconds.
rrule (str, optional) – The recurrence rules as defined in the iCalendar RFC 5545. The supported rules for SLO corrections are FREQ , INTERVAL , COUNT , UNTIL and BYDAY.
start (int, optional) – Starting time of the correction in epoch seconds.
timezone (str, optional) – The timezone to display in the UI for the correction times (defaults to “UTC”).

slo_creator¶

class SLOCreator(*args, **kwargs)¶

Bases: ModelNormal

The creator of the SLO

Parameters:

email (str, optional) – Email of the creator.
id (int, optional) – User ID of the creator.
name (str, none_type, optional) – Name of the creator.

slo_data_source_query_definition¶

class SLODataSourceQueryDefinition(*args, **kwargs)¶

Bases: ModelComposed

A formula and function query.

Parameters:

aggregator (FormulaAndFunctionMetricAggregation, optional) – The aggregation methods available for metrics queries.
data_source (FormulaAndFunctionMetricDataSource) – Data source for metrics queries.
name (str) – Name of the query for use in formulas.
query (str) – Metrics query definition.

slo_delete_response¶

class SLODeleteResponse(*args, **kwargs)¶

Bases: ModelNormal

A response list of all service level objective deleted.

Parameters:

data ([str], optional) – An array containing the ID of the deleted service level objective object.
errors ({str: (str,)}, optional) – An dictionary containing the ID of the SLO as key and a deletion error as value.

slo_error_budget_remaining_data¶

class SLOErrorBudgetRemainingData(*args, **kwargs)¶

Bases: ModelNormal

A mapping of threshold timeframe to the remaining error budget.

slo_error_timeframe¶

class SLOErrorTimeframe(*args, **kwargs)¶

Bases: ModelSimple

The timeframe of the threshold associated with this error: or “all” if all thresholds are affected.

Parameters:

value (str) – Must be one of [“7d”, “30d”, “90d”, “all”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_formula¶

class SLOFormula(*args, **kwargs)¶

Bases: ModelNormal

A formula that specifies how to combine the results of multiple queries.

Parameters:: formula (str) – The formula string, which is an expression involving named queries.

slo_history_metrics¶

class SLOHistoryMetrics(*args, **kwargs)¶

Bases: ModelNormal

A metric based SLO history response.

This is not included in responses for monitor based SLOs.

Parameters:

denominator (SLOHistoryMetricsSeries) – A representation of metric based SLO time series for the provided queries. This is the same response type from batch_query endpoint.
interval (int) – The aggregated query interval for the series data. It’s implicit based on the query time window.
message (str, optional) – Optional message if there are specific query issues/warnings.
numerator (SLOHistoryMetricsSeries) – A representation of metric based SLO time series for the provided queries. This is the same response type from batch_query endpoint.
query (str) – The combined numerator and denominator query CSV.
res_type (str) – The series result type. This mimics batch_query response type.
resp_version (int) – The series response version type. This mimics batch_query response type.
times ([float]) – An array of query timestamps in EPOCH milliseconds.

slo_history_metrics_series¶

class SLOHistoryMetricsSeries(*args, **kwargs)¶

Bases: ModelNormal

A representation of metric based SLO time series for the provided queries. This is the same response type from batch_query endpoint.

Parameters:

count (int) – Count of submitted metrics.
metadata (SLOHistoryMetricsSeriesMetadata, optional) – Query metadata.
sum (float) – Total sum of the query.
values ([float]) – The query values for each metric.

slo_history_metrics_series_metadata¶

class SLOHistoryMetricsSeriesMetadata(*args, **kwargs)¶

Bases: ModelNormal

Query metadata.

Parameters:

aggr (str, optional) – Query aggregator function.
expression (str, optional) – Query expression.
metric (str, optional) – Query metric used.
query_index (int, optional) – Query index from original combined query.
scope (str, optional) – Query scope.
unit ([SLOHistoryMetricsSeriesMetadataUnit, none_type], none_type, optional) – An array of metric units that contains up to two unit objects. For example, bytes represents one unit object and bytes per second represents two unit objects. If a metric query only has one unit object, the second array element is null.

slo_history_metrics_series_metadata_unit¶

class SLOHistoryMetricsSeriesMetadataUnit(*args, **kwargs)¶

Bases: ModelNormal

An Object of metric units.

Parameters:

family (str, optional) – The family of metric unit, for example bytes is the family for kibibyte , byte , and bit units.
id (int, optional) – The ID of the metric unit.
name (str, optional) – The unit of the metric, for instance byte.
plural (str, none_type, optional) – The plural Unit of metric, for instance bytes.
scale_factor (float, optional) – The scale factor of metric unit, for instance 1.0.
short_name (str, none_type, optional) – A shorter and abbreviated version of the metric unit, for instance B.

slo_history_monitor¶

class SLOHistoryMonitor(*args, **kwargs)¶

Bases: ModelNormal

An object that holds an SLI value and its associated data. It can represent an SLO’s overall SLI value. This can also represent the SLI value for a specific monitor in multi-monitor SLOs, or a group in grouped SLOs.

Parameters:

error_budget_remaining (SLOErrorBudgetRemainingData, optional) – A mapping of threshold timeframe to the remaining error budget.
errors ([SLOHistoryResponseErrorWithType], optional) – An array of error objects returned while querying the history data for the service level objective.
group (str, optional) – For groups in a grouped SLO, this is the group name.
history ([[float]], optional) – For monitor based SLOs, this includes the aggregated history as arrays that include time series and uptime data where 0=monitor is in OK state and 1=monitor is in alert state.
monitor_modified (int, optional) – For monitor based SLOs, this is the last modified timestamp in epoch seconds of the monitor.
monitor_type (str, optional) – For monitor based SLOs, this describes the type of monitor.
name (str, optional) – For groups in a grouped SLO, this is the group name. For monitors in a multi-monitor SLO, this is the monitor name.
precision (float, optional) – The amount of decimal places the SLI value is accurate to for the given from && to timestamp. Use span_precision instead. Deprecated.
preview (bool, optional) – For monitor based SLOs, when true this indicates that a replay is in progress to give an accurate uptime calculation.
sli_value (float, none_type, optional) – The current SLI value of the SLO over the history window.
span_precision (float, optional) – The amount of decimal places the SLI value is accurate to for the given from && to timestamp.
uptime (float, optional) – Use sli_value instead. Deprecated.

slo_history_response¶

class SLOHistoryResponse(*args, **kwargs)¶

Bases: ModelNormal

A service level objective history response.

Parameters:

data (SLOHistoryResponseData, optional) – An array of service level objective objects.
errors ([SLOHistoryResponseError], none_type, optional) – A list of errors while querying the history data for the service level objective.

slo_history_response_data¶

class SLOHistoryResponseData(*args, **kwargs)¶

Bases: ModelNormal

An array of service level objective objects.

Parameters:

from_ts (int, optional) – The from timestamp in epoch seconds.
group_by ([str], optional) –
For metric based SLOs where the query includes a group-by clause, this represents the list of grouping parameters.

This is not included in responses for monitor based SLOs.
groups ([SLOHistoryMonitor], optional) –
For grouped SLOs, this represents SLI data for specific groups.

This is not included in the responses for metric based SLOs.
monitors ([SLOHistoryMonitor], optional) –
For multi-monitor SLOs, this represents SLI data for specific monitors.

This is not included in the responses for metric based SLOs.
overall (SLOHistorySLIData, optional) – An object that holds an SLI value and its associated data. It can represent an SLO’s overall SLI value. This can also represent the SLI value for a specific monitor in multi-monitor SLOs, or a group in grouped SLOs.
series (SLOHistoryMetrics, optional) –
A metric based SLO history response.

This is not included in responses for monitor based SLOs.
thresholds ({str: (SLOThreshold,)}, optional) – mapping of string timeframe to the SLO threshold.
to_ts (int, optional) – The to timestamp in epoch seconds.
type (SLOType, optional) – The type of the service level objective.
type_id (SLOTypeNumeric, optional) – A numeric representation of the type of the service level objective ( 0 for monitor, 1 for metric). Always included in service level objective responses. Ignored in create/update requests.

slo_history_response_error¶

class SLOHistoryResponseError(*args, **kwargs)¶

Bases: ModelNormal

A list of errors while querying the history data for the service level objective.

Parameters:: error (str, optional) – Human readable error.

slo_history_response_error_with_type¶

class SLOHistoryResponseErrorWithType(*args, **kwargs)¶

Bases: ModelNormal

An object describing the error with error type and error message.

Parameters:

error_message (str) – A message with more details about the error.
error_type (str) – Type of the error.

slo_history_sli_data¶

class SLOHistorySLIData(*args, **kwargs)¶

Bases: ModelNormal

An object that holds an SLI value and its associated data. It can represent an SLO’s overall SLI value. This can also represent the SLI value for a specific monitor in multi-monitor SLOs, or a group in grouped SLOs.

Parameters:

error_budget_remaining (SLOErrorBudgetRemainingData, optional) – A mapping of threshold timeframe to the remaining error budget.
errors ([SLOHistoryResponseErrorWithType], optional) – An array of error objects returned while querying the history data for the service level objective.
group (str, optional) – For groups in a grouped SLO, this is the group name.
history ([[float]], optional) – For monitor based SLOs, this includes the aggregated history as arrays that include time series and uptime data where 0=monitor is in OK state and 1=monitor is in alert state.
monitor_modified (int, optional) – For monitor based SLOs, this is the last modified timestamp in epoch seconds of the monitor.
monitor_type (str, optional) – For monitor based SLOs, this describes the type of monitor.
name (str, optional) – For groups in a grouped SLO, this is the group name. For monitors in a multi-monitor SLO, this is the monitor name.
precision ({str: (float,)}, optional) – A mapping of threshold timeframe to number of accurate decimals, regardless of the from && to timestamp.
preview (bool, optional) – For monitor based SLOs, when true this indicates that a replay is in progress to give an accurate uptime calculation.
sli_value (float, none_type, optional) – The current SLI value of the SLO over the history window.
span_precision (float, optional) – The amount of decimal places the SLI value is accurate to for the given from && to timestamp.
uptime (float, none_type, optional) – Use sli_value instead. Deprecated.

slo_list_response¶

class SLOListResponse(*args, **kwargs)¶

Bases: ModelNormal

A response with one or more service level objective.

Parameters:

data ([ServiceLevelObjective], optional) – An array of service level objective objects.
errors ([str], optional) – An array of error messages. Each endpoint documents how/whether this field is used.
metadata (SLOListResponseMetadata, optional) – The metadata object containing additional information about the list of SLOs.

slo_list_response_metadata¶

class SLOListResponseMetadata(*args, **kwargs)¶

Bases: ModelNormal

The metadata object containing additional information about the list of SLOs.

Parameters:: page (SLOListResponseMetadataPage, optional) – The object containing information about the pages of the list of SLOs.

slo_list_response_metadata_page¶

class SLOListResponseMetadataPage(*args, **kwargs)¶

Bases: ModelNormal

The object containing information about the pages of the list of SLOs.

Parameters:

total_count (int, optional) – The total number of resources that could be retrieved ignoring the parameters and filters in the request.
total_filtered_count (int, optional) – The total number of resources that match the parameters and filters in the request. This attribute can be used by a client to determine the total number of pages.

slo_list_widget_definition¶

class SLOListWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

Use the SLO List widget to track your SLOs (Service Level Objectives) on dashboards.

Parameters:

requests ([SLOListWidgetRequest]) – Array of one request object to display in the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (SLOListWidgetDefinitionType) – Type of the SLO List widget.

slo_list_widget_definition_type¶

class SLOListWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the SLO List widget.

Parameters:

value (str) – If omitted defaults to “slo_list”. Must be one of [“slo_list”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_list_widget_query¶

class SLOListWidgetQuery(*args, **kwargs)¶

Bases: ModelNormal

Updated SLO List widget.

Parameters:

limit (int, optional) – Maximum number of results to display in the table.
query_string (str) – Widget query.
sort ([WidgetFieldSort], optional) – Options for sorting results.

slo_list_widget_request¶

class SLOListWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated SLO List widget.

Parameters:

query (SLOListWidgetQuery) – Updated SLO List widget.
request_type (SLOListWidgetRequestType) – Widget request type.

slo_list_widget_request_type¶

class SLOListWidgetRequestType(*args, **kwargs)¶

Bases: ModelSimple

Widget request type.

Parameters:

value (str) – If omitted defaults to “slo_list”. Must be one of [“slo_list”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_overall_statuses¶

class SLOOverallStatuses(*args, **kwargs)¶

Bases: ModelNormal

Overall status of the SLO by timeframes.

Parameters:

error (str, none_type, optional) – Error message if SLO status or error budget could not be calculated.
error_budget_remaining (float, none_type, optional) – Remaining error budget of the SLO in percentage.
indexed_at (int, optional) – timestamp (UNIX time in seconds) of when the SLO status and error budget were calculated.
raw_error_budget_remaining (SLORawErrorBudgetRemaining, none_type, optional) – Error budget remaining for an SLO.
span_precision (int, none_type, optional) – The amount of decimal places the SLI value is accurate to.
state (SLOState, optional) – State of the SLO.
status (float, none_type, optional) – The status of the SLO.
target (float, optional) – The target of the SLO.
timeframe (SLOTimeframe, optional) – The SLO time window options.

slo_raw_error_budget_remaining¶

class SLORawErrorBudgetRemaining(*args, **kwargs)¶

Bases: ModelNormal

Error budget remaining for an SLO.

Parameters:

unit (str, optional) – Error budget remaining unit.
value (float, optional) – Error budget remaining value.

slo_response¶

class SLOResponse(*args, **kwargs)¶

Bases: ModelNormal

A service level objective response containing a single service level objective.

Parameters:

data (SLOResponseData, optional) – A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , tags , etc.).
errors ([str], optional) – An array of error messages. Each endpoint documents how/whether this field is used.

slo_response_data¶

class SLOResponseData(*args, **kwargs)¶

Bases: ModelNormal

A service level objective object includes a service level indicator, thresholds for one or more timeframes, and metadata ( name , description , tags , etc.).

Parameters:

configured_alert_ids ([int], optional) – A list of SLO monitors IDs that reference this SLO. This field is returned only when with_configured_alert_ids parameter is true in query.
created_at (int, optional) –
Creation timestamp (UNIX time in seconds)

Always included in service level objective responses.
creator (Creator, optional) – Object describing the creator of the shared element.
description (str, none_type, optional) –
A user-defined description of the service level objective.

Always included in service level objective responses (but may be null ). Optional in create/update requests.
groups ([str], optional) –
A list of (up to 20) monitor groups that narrow the scope of a monitor service level objective.

Included in service level objective responses if it is not empty. Optional in create/update requests for monitor service level objectives, but may only be used when then length of the monitor_ids field is one.
id (str, optional) –
A unique identifier for the service level objective object.

Always included in service level objective responses.
modified_at (int, optional) –
Modification timestamp (UNIX time in seconds)

Always included in service level objective responses.
monitor_ids ([int], optional) – A list of monitor ids that defines the scope of a monitor service level objective. Required if type is monitor.
monitor_tags ([str], optional) – The union of monitor tags for all monitors referenced by the monitor_ids field. Always included in service level objective responses for monitor service level objectives (but may be empty). Ignored in create/update requests. Does not affect which monitors are included in the service level objective (that is determined entirely by the monitor_ids field).
name (str, optional) – The name of the service level objective object.
query (ServiceLevelObjectiveQuery, optional) – A metric-based SLO. Required if type is metric. Note that Datadog only allows the sum by aggregator to be used because this will sum up all request counts instead of averaging them, or taking the max or min of all of those requests.
sli_specification (SLOSliSpec, optional) – A generic SLI specification. This is currently used for time-slice SLOs only.
tags ([str], optional) – A list of tags associated with this service level objective. Always included in service level objective responses (but may be empty). Optional in create/update requests.
target_threshold (float, optional) – The target threshold such that when the service level indicator is above this threshold over the given timeframe, the objective is being met.
thresholds ([SLOThreshold], optional) – The thresholds (timeframes and associated targets) for this service level objective object.
timeframe (SLOTimeframe, optional) – The SLO time window options.
type (SLOType, optional) – The type of the service level objective.
warning_threshold (float, optional) – The optional warning threshold such that when the service level indicator is below this value for the given threshold, but above the target threshold, the objective appears in a “warning” state. This value must be greater than the target threshold.

slo_sli_spec¶

class SLOSliSpec(*args, **kwargs)¶

Bases: ModelComposed

A generic SLI specification. This is currently used for time-slice SLOs only.

Parameters:: time_slice (SLOTimeSliceCondition) – The time-slice condition, composed of 3 parts: 1. the metric timeseries query, 2. the comparator, and 3. the threshold.

slo_state¶

class SLOState(*args, **kwargs)¶

Bases: ModelSimple

State of the SLO.

Parameters:

value (str) – Must be one of [“breached”, “warning”, “ok”, “no_data”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_status¶

class SLOStatus(*args, **kwargs)¶

Bases: ModelNormal

Status of the SLO’s primary timeframe.

Parameters:

calculation_error (str, none_type, optional) – Error message if SLO status or error budget could not be calculated.
error_budget_remaining (float, none_type, optional) – Remaining error budget of the SLO in percentage.
indexed_at (int, optional) – timestamp (UNIX time in seconds) of when the SLO status and error budget were calculated.
raw_error_budget_remaining (SLORawErrorBudgetRemaining, none_type, optional) – Error budget remaining for an SLO.
sli (float, none_type, optional) – The current service level indicator (SLI) of the SLO, also known as ‘status’. This is a percentage value from 0-100 (inclusive).
span_precision (int, none_type, optional) – The number of decimal places the SLI value is accurate to.
state (SLOState, optional) – State of the SLO.

slo_threshold¶

class SLOThreshold(*args, **kwargs)¶

Bases: ModelNormal

SLO thresholds (target and optionally warning) for a single time window.

Parameters:

target (float) – The target value for the service level indicator within the corresponding timeframe.
target_display (str, optional) –
A string representation of the target that indicates its precision. It uses trailing zeros to show significant decimal places (for example 98.00 ).

Always included in service level objective responses. Ignored in create/update requests.
timeframe (SLOTimeframe) – The SLO time window options.
warning (float, optional) – The warning value for the service level objective.
warning_display (str, optional) –
A string representation of the warning target (see the description of the target_display field for details).

Included in service level objective responses if a warning target exists. Ignored in create/update requests.

slo_time_slice_comparator¶

class SLOTimeSliceComparator(*args, **kwargs)¶

Bases: ModelSimple

The comparator used to compare the SLI value to the threshold.

Parameters:

value (str) – Must be one of [“>”, “>=”, “<”, “<=”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_time_slice_condition¶

class SLOTimeSliceCondition(*args, **kwargs)¶

Bases: ModelNormal

The time-slice condition, composed of 3 parts: 1. the metric timeseries query, 2. the comparator, and 3. the threshold.

Parameters:

comparator (SLOTimeSliceComparator) – The comparator used to compare the SLI value to the threshold.
query (SLOTimeSliceQuery) – The queries and formula used to calculate the SLI value.
threshold (float) – The threshold value to which each SLI value will be compared.

slo_time_slice_query¶

class SLOTimeSliceQuery(*args, **kwargs)¶

Bases: ModelNormal

The queries and formula used to calculate the SLI value.

Parameters:

formulas ([SLOFormula]) – A list that contains exactly one formula, as only a single formula may be used in a time-slice SLO.
queries ([SLODataSourceQueryDefinition]) – A list of queries that are used to calculate the SLI value.

slo_time_slice_spec¶

class SLOTimeSliceSpec(*args, **kwargs)¶

Bases: ModelNormal

A time-slice SLI specification.

Parameters:: time_slice (SLOTimeSliceCondition) – The time-slice condition, composed of 3 parts: 1. the metric timeseries query, 2. the comparator, and 3. the threshold.

slo_timeframe¶

class SLOTimeframe(*args, **kwargs)¶

Bases: ModelSimple

The SLO time window options.

Parameters:

value (str) – Must be one of [“7d”, “30d”, “90d”, “custom”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_type¶

class SLOType(*args, **kwargs)¶

Bases: ModelSimple

The type of the service level objective.

Parameters:

value (str) – Must be one of [“metric”, “monitor”, “time_slice”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_type_numeric¶

class SLOTypeNumeric(*args, **kwargs)¶

Bases: ModelSimple

A numeric representation of the type of the service level objective (0 for: monitor, 1 for metric). Always included in service level objective responses. Ignored in create/update requests.

Parameters:

value (int) – Must be one of [0, 1, 2].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

slo_widget_definition¶

class SLOWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

Use the SLO and uptime widget to track your SLOs (Service Level Objectives) and uptime on screenboards and timeboards.

Parameters:

additional_query_filters (str, optional) – Additional filters applied to the SLO query.
global_time_target (str, optional) – Defined global time target.
show_error_budget (bool, optional) – Defined error budget.
slo_id (str, optional) – ID of the SLO displayed.
time_windows ([WidgetTimeWindows], optional) – Times being monitored.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (SLOWidgetDefinitionType) – Type of the SLO widget.
view_mode (WidgetViewMode, optional) – Define how you want the SLO to be displayed.
view_type (str) – Type of view displayed by the widget.

slo_widget_definition_type¶

class SLOWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the SLO widget.

Parameters:

value (str) – If omitted defaults to “slo”. Must be one of [“slo”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

split_config¶

class SplitConfig(*args, **kwargs)¶

Bases: ModelNormal

Encapsulates all user choices about how to split a graph.

Parameters:

limit (int) – Maximum number of graphs to display in the widget.
sort (SplitSort) – Controls the order in which graphs appear in the split.
split_dimensions ([SplitDimension]) – The dimension(s) on which to split the graph
static_splits ([[SplitVectorEntryItem]], optional) – Manual selection of tags making split graph widget static

split_config_sort_compute¶

class SplitConfigSortCompute(*args, **kwargs)¶

Bases: ModelNormal

Defines the metric and aggregation used as the sort value.

Parameters:

aggregation (str) – How to aggregate the sort metric for the purposes of ordering.
metric (str) – The metric to use for sorting graphs.

split_dimension¶

class SplitDimension(*args, **kwargs)¶

Bases: ModelNormal

The property by which the graph splits

Parameters:: one_graph_per (str) – The system interprets this attribute differently depending on the data source of the query being split. For metrics, it’s a tag. For the events platform, it’s an attribute or tag.

split_graph_source_widget_definition¶

class SplitGraphSourceWidgetDefinition(*args, **kwargs)¶

Bases: ModelComposed

The original widget we are splitting on.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
requests ([ChangeWidgetRequest]) –
Array of one request object to display in the widget.

See the dedicated [Request JSON schema documentation](https://docs.datadoghq.com/dashboards/graphing_json/request_json)
to learn how to build the REQUEST_SCHEMA.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (ChangeWidgetDefinitionType) – Type of the change widget.
style (GeomapWidgetDefinitionStyle) – The style to apply to the widget.
view (GeomapWidgetDefinitionView) – The view of the world that the map should render.
autoscale (bool, optional) – Whether to use auto-scaling or not.
custom_unit (str, optional) – Display a unit of your choice on the widget.
precision (int, optional) – Number of decimals to show. If not defined, the widget uses the raw value.
text_align (WidgetTextAlign, optional) – How to align the text on the widget.
timeseries_background (TimeseriesBackground, optional) – Set a timeseries on the widget background.
color_by_groups ([str], optional) – List of groups used for colors.
xaxis (WidgetAxis, optional) – Axis controls for the widget.
yaxis (WidgetAxis, optional) – Axis controls for the widget.
hide_total (bool, optional) – Show the total value in this widget.
legend (SunburstWidgetLegend, optional) – Configuration of the legend.
has_search_bar (TableWidgetHasSearchBar, optional) – Controls the display of the search bar.
events ([WidgetEvent], optional) – List of widget events.
legend_columns ([TimeseriesWidgetLegendColumn], optional) – Columns displayed in the legend.
legend_layout (TimeseriesWidgetLegendLayout, optional) – Layout of the legend.
legend_size (str, optional) – Available legend sizes for a widget. Should be one of “0”, “2”, “4”, “8”, “16”, or “auto”.
markers ([WidgetMarker], optional) – List of markers.
right_yaxis (WidgetAxis, optional) – Axis controls for the widget.
show_legend (bool, optional) – (screenboard only) Show the legend for this widget.
color_by (TreeMapColorBy, optional) – (deprecated) The attribute formerly used to determine color in the widget.
group_by (TreeMapGroupBy, optional) – (deprecated) The attribute formerly used to group elements in the widget.
size_by (TreeMapSizeBy, optional) – (deprecated) The attribute formerly used to determine size in the widget.

split_graph_viz_size¶

class SplitGraphVizSize(*args, **kwargs)¶

Bases: ModelSimple

Size of the individual graphs in the split.

Parameters:

value (str) – Must be one of [“xs”, “sm”, “md”, “lg”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

split_graph_widget_definition¶

class SplitGraphWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The split graph widget allows you to create repeating units of a graph - one for each value in a group (for example: one per service)

Parameters:

has_uniform_y_axes (bool, optional) – Normalize y axes across graphs
size (SplitGraphVizSize) – Size of the individual graphs in the split.
source_widget_definition (SplitGraphSourceWidgetDefinition) – The original widget we are splitting on.
split_config (SplitConfig) – Encapsulates all user choices about how to split a graph.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of your widget.
type (SplitGraphWidgetDefinitionType) – Type of the split graph widget

split_graph_widget_definition_type¶

class SplitGraphWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the split graph widget

Parameters:

value (str) – If omitted defaults to “split_group”. Must be one of [“split_group”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

split_sort¶

class SplitSort(*args, **kwargs)¶

Bases: ModelNormal

Controls the order in which graphs appear in the split.

Parameters:

compute (SplitConfigSortCompute, optional) – Defines the metric and aggregation used as the sort value.
order (WidgetSort) – Widget sorting methods.

split_vector_entry_item¶

class SplitVectorEntryItem(*args, **kwargs)¶

Bases: ModelNormal

The split graph list contains a graph for each value of the split dimension.

Parameters:

tag_key (str) – The tag key.
tag_values ([str]) – The tag values.

successful_signal_update_response¶

class SuccessfulSignalUpdateResponse(*args, **kwargs)¶

Bases: ModelNormal

Updated signal data following a successfully performed update.

Parameters:: status (str, optional) – Status of the response.

sunburst_widget_definition¶

class SunburstWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

Sunbursts are spot on to highlight how groups contribute to the total of a query.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
hide_total (bool, optional) – Show the total value in this widget.
legend (SunburstWidgetLegend, optional) – Configuration of the legend.
requests ([SunburstWidgetRequest]) – List of sunburst widget requests.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of your widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (SunburstWidgetDefinitionType) – Type of the Sunburst widget.

sunburst_widget_definition_type¶

class SunburstWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the Sunburst widget.

Parameters:

value (str) – If omitted defaults to “sunburst”. Must be one of [“sunburst”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

sunburst_widget_legend¶

class SunburstWidgetLegend(*args, **kwargs)¶

Bases: ModelComposed

Configuration of the legend.

Parameters:

type (SunburstWidgetLegendTableType) – Whether or not to show a table legend.
hide_percent (bool, optional) – Whether to hide the percentages of the groups.
hide_value (bool, optional) – Whether to hide the values of the groups.

sunburst_widget_legend_inline_automatic¶

class SunburstWidgetLegendInlineAutomatic(*args, **kwargs)¶

Bases: ModelNormal

Configuration of inline or automatic legends.

Parameters:

hide_percent (bool, optional) – Whether to hide the percentages of the groups.
hide_value (bool, optional) – Whether to hide the values of the groups.
type (SunburstWidgetLegendInlineAutomaticType) – Whether to show the legend inline or let it be automatically generated.

sunburst_widget_legend_inline_automatic_type¶

class SunburstWidgetLegendInlineAutomaticType(*args, **kwargs)¶

Bases: ModelSimple

Whether to show the legend inline or let it be automatically generated.

Parameters:

value (str) – Must be one of [“inline”, “automatic”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

sunburst_widget_legend_table¶

class SunburstWidgetLegendTable(*args, **kwargs)¶

Bases: ModelNormal

Configuration of table-based legend.

Parameters:: type (SunburstWidgetLegendTableType) – Whether or not to show a table legend.

sunburst_widget_legend_table_type¶

class SunburstWidgetLegendTableType(*args, **kwargs)¶

Bases: ModelSimple

Whether or not to show a table legend.

Parameters:

value (str) – Must be one of [“table”, “none”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

sunburst_widget_request¶

class SunburstWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Request definition of sunburst widget.

Parameters:

apm_query (LogQueryDefinition, optional) – The log query.
audit_query (LogQueryDefinition, optional) – The log query.
event_query (LogQueryDefinition, optional) – The log query.
formulas ([WidgetFormula], optional) – List of formulas that operate on queries.
log_query (LogQueryDefinition, optional) – The log query.
network_query (LogQueryDefinition, optional) – The log query.
process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.
profile_metrics_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – Widget query.
queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.
response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.
style (WidgetStyle, optional) – Widget style definition.

synthetics_api_step¶

class SyntheticsAPIStep(*args, **kwargs)¶

Bases: ModelNormal

The steps used in a Synthetic multistep API test.

Parameters:

allow_failure (bool, optional) – Determines whether or not to continue with test if this step fails.
assertions ([SyntheticsAssertion]) – Array of assertions used for the test.
extracted_values ([SyntheticsParsingOptions], optional) – Array of values to parse and save as variables from the response.
is_critical (bool, optional) – Determines whether or not to consider the entire test as failed if this step fails. Can be used only if allowFailure is true.
name (str) – The name of the step.
request (SyntheticsTestRequest) – Object describing the Synthetic test request.
retry (SyntheticsTestOptionsRetry, optional) – Object describing the retry strategy to apply to a Synthetic test.
subtype (SyntheticsAPIStepSubtype) – The subtype of the Synthetic multistep API test step, currently only supporting http.

synthetics_api_step_subtype¶

class SyntheticsAPIStepSubtype(*args, **kwargs)¶

Bases: ModelSimple

The subtype of the Synthetic multistep API test step, currently only supporting http.

Parameters:

value (str) – If omitted defaults to “http”. Must be one of [“http”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_api_test¶

class SyntheticsAPITest(*args, **kwargs)¶

Bases: ModelNormal

Object containing details about a Synthetic API test.

Parameters:

config (SyntheticsAPITestConfig) – Configuration object for a Synthetic API test.
locations ([str]) – Array of locations used to run the test.
message (str) – Notification message associated with the test.
monitor_id (int, optional) – The associated monitor ID.
name (str) – Name of the test.
options (SyntheticsTestOptions) – Object describing the extra options for a Synthetic test.
public_id (str, optional) – The public ID for the test.
status (SyntheticsTestPauseStatus, optional) – Define whether you want to start ( live ) or pause ( paused ) a Synthetic test.
subtype (SyntheticsTestDetailsSubType, optional) – The subtype of the Synthetic API test, http , ssl , tcp , dns , icmp , udp , websocket , grpc or multi.
tags ([str], optional) – Array of tags attached to the test.
type (SyntheticsAPITestType) – Type of the Synthetic test, api.

synthetics_api_test_config¶

class SyntheticsAPITestConfig(*args, **kwargs)¶

Bases: ModelNormal

Configuration object for a Synthetic API test.

Parameters:

assertions ([SyntheticsAssertion], optional) – Array of assertions used for the test. Required for single API tests.
config_variables ([SyntheticsConfigVariable], optional) – Array of variables used for the test.
request (SyntheticsTestRequest, optional) – Object describing the Synthetic test request.
steps ([SyntheticsAPIStep], optional) – When the test subtype is multi , the steps of the test.

synthetics_api_test_failure_code¶

class SyntheticsApiTestFailureCode(*args, **kwargs)¶

Bases: ModelSimple

Error code that can be returned by a Synthetic test.

Parameters:

value (str) – Must be one of [“BODY_TOO_LARGE”, “DENIED”, “TOO_MANY_REDIRECTS”, “AUTHENTICATION_ERROR”, “DECRYPTION”, “INVALID_CHAR_IN_HEADER”, “HEADER_TOO_LARGE”, “HEADERS_INCOMPATIBLE_CONTENT_LENGTH”, “INVALID_REQUEST”, “REQUIRES_UPDATE”, “UNESCAPED_CHARACTERS_IN_REQUEST_PATH”, “MALFORMED_RESPONSE”, “INCORRECT_ASSERTION”, “CONNREFUSED”, “CONNRESET”, “DNS”, “HOSTUNREACH”, “NETUNREACH”, “TIMEOUT”, “SSL”, “OCSP”, “INVALID_TEST”, “TUNNEL”, “WEBSOCKET”, “UNKNOWN”, “INTERNAL_ERROR”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_api_test_result_data¶

class SyntheticsAPITestResultData(*args, **kwargs)¶

Bases: ModelNormal

Object containing results for your Synthetic API test.

Parameters:

cert (SyntheticsSSLCertificate, optional) – Object describing the SSL certificate used for a Synthetic test.
event_type (SyntheticsTestProcessStatus, optional) – Status of a Synthetic test.
failure (SyntheticsApiTestResultFailure, optional) – The API test failure details.
http_status_code (int, optional) – The API test HTTP status code.
request_headers ({str: (dict,)}, optional) – Request header object used for the API test.
response_body (str, optional) – Response body returned for the API test.
response_headers ({str: (bool, date, datetime, dict, float, int, list, str, UUID, none_type,)}, optional) – Response headers returned for the API test.
response_size (int, optional) – Global size in byte of the API test response.
timings (SyntheticsTiming, optional) – Object containing all metrics and their values collected for a Synthetic API test. See the Synthetic Monitoring Metrics documentation.

synthetics_api_test_result_failure¶

class SyntheticsApiTestResultFailure(*args, **kwargs)¶

Bases: ModelNormal

The API test failure details.

Parameters:

code (SyntheticsApiTestFailureCode, optional) – Error code that can be returned by a Synthetic test.
message (str, optional) – The API test error message.

synthetics_api_test_result_full¶

class SyntheticsAPITestResultFull(*args, **kwargs)¶

Bases: ModelNormal

Object returned describing a API test result.

Parameters:

check (SyntheticsAPITestResultFullCheck, optional) – Object describing the API test configuration.
check_time (float, optional) – When the API test was conducted.
check_version (int, optional) – Version of the API test used.
probe_dc (str, optional) – Locations for which to query the API test results.
result (SyntheticsAPITestResultData, optional) – Object containing results for your Synthetic API test.
result_id (str, optional) – ID of the API test result.
status (SyntheticsTestMonitorStatus, optional) –
The status of your Synthetic monitor.
- O for not triggered
- 1 for triggered
- 2 for no data

synthetics_api_test_result_full_check¶

class SyntheticsAPITestResultFullCheck(*args, **kwargs)¶

Bases: ModelNormal

Object describing the API test configuration.

Parameters:: config (SyntheticsTestConfig) – Configuration object for a Synthetic test.

synthetics_api_test_result_short¶

class SyntheticsAPITestResultShort(*args, **kwargs)¶

Bases: ModelNormal

Object with the results of a single Synthetic API test.

Parameters:

check_time (float, optional) – Last time the API test was performed.
probe_dc (str, optional) – Location from which the API test was performed.
result (SyntheticsAPITestResultShortResult, optional) – Result of the last API test run.
result_id (str, optional) – ID of the API test result.
status (SyntheticsTestMonitorStatus, optional) –
The status of your Synthetic monitor.
- O for not triggered
- 1 for triggered
- 2 for no data

synthetics_api_test_result_short_result¶

class SyntheticsAPITestResultShortResult(*args, **kwargs)¶

Bases: ModelNormal

Result of the last API test run.

Parameters:

passed (bool, optional) – Describes if the test run has passed or failed.
timings (SyntheticsTiming, optional) –
Object containing all metrics and their values collected for a Synthetic API test. See the Synthetic Monitoring Metrics documentation.

synthetics_api_test_type¶

class SyntheticsAPITestType(*args, **kwargs)¶

Bases: ModelSimple

Type of the Synthetic test, api.

Parameters:

value (str) – If omitted defaults to “api”. Must be one of [“api”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_assertion¶

class SyntheticsAssertion(*args, **kwargs)¶

Bases: ModelComposed

Object describing the assertions type, their associated operator, which property they apply, and upon which target.

Parameters:

operator (SyntheticsAssertionOperator) – Assertion operator to apply.
_property (str, optional) – The associated assertion property.
target (bool, date, datetime, dict, float, int, list, str, UUID, none_type) – Value used by the operator.
timings_scope (SyntheticsAssertionTimingsScope, optional) – Timings scope for response time assertions.
type (SyntheticsAssertionType) – Type of the assertion.

synthetics_assertion_json_path_operator¶

class SyntheticsAssertionJSONPathOperator(*args, **kwargs)¶

Bases: ModelSimple

Assertion operator to apply.

Parameters:

value (str) – If omitted defaults to “validatesJSONPath”. Must be one of [“validatesJSONPath”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_assertion_json_path_target¶

class SyntheticsAssertionJSONPathTarget(*args, **kwargs)¶

Bases: ModelNormal

An assertion for the validatesJSONPath operator.

Parameters:

operator (SyntheticsAssertionJSONPathOperator) – Assertion operator to apply.
_property (str, optional) – The associated assertion property.
target (SyntheticsAssertionJSONPathTargetTarget, optional) – Composed target for validatesJSONPath operator.
type (SyntheticsAssertionType) – Type of the assertion.

synthetics_assertion_json_path_target_target¶

class SyntheticsAssertionJSONPathTargetTarget(*args, **kwargs)¶

Bases: ModelNormal

Composed target for validatesJSONPath operator.

Parameters:

json_path (str, optional) – The JSON path to assert.
operator (str, optional) – The specific operator to use on the path.
target_value (bool, date, datetime, dict, float, int, list, str, UUID, none_type, optional) – The path target value to compare to.

synthetics_assertion_operator¶

class SyntheticsAssertionOperator(*args, **kwargs)¶

Bases: ModelSimple

Assertion operator to apply.

Parameters:

value (str) – Must be one of [“contains”, “doesNotContain”, “is”, “isNot”, “lessThan”, “lessThanOrEqual”, “moreThan”, “moreThanOrEqual”, “matches”, “doesNotMatch”, “validates”, “isInMoreThan”, “isInLessThan”, “doesNotExist”, “isUndefined”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_assertion_target¶

class SyntheticsAssertionTarget(*args, **kwargs)¶

Bases: ModelNormal

An assertion which uses a simple target.

Parameters:

operator (SyntheticsAssertionOperator) – Assertion operator to apply.
_property (str, optional) – The associated assertion property.
target (bool, date, datetime, dict, float, int, list, str, UUID, none_type) – Value used by the operator.
timings_scope (SyntheticsAssertionTimingsScope, optional) – Timings scope for response time assertions.
type (SyntheticsAssertionType) – Type of the assertion.

synthetics_assertion_timings_scope¶

class SyntheticsAssertionTimingsScope(*args, **kwargs)¶

Bases: ModelSimple

Timings scope for response time assertions.

Parameters:

value (str) – Must be one of [“all”, “withoutDNS”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_assertion_type¶

class SyntheticsAssertionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the assertion.

Parameters:

value (str) – Must be one of [“body”, “header”, “statusCode”, “certificate”, “responseTime”, “property”, “recordEvery”, “recordSome”, “tlsVersion”, “minTlsVersion”, “latency”, “packetLossPercentage”, “packetsReceived”, “networkHop”, “receivedMessage”, “grpcHealthcheckStatus”, “grpcMetadata”, “grpcProto”, “connection”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_assertion_x_path_operator¶

class SyntheticsAssertionXPathOperator(*args, **kwargs)¶

Bases: ModelSimple

Assertion operator to apply.

Parameters:

value (str) – If omitted defaults to “validatesXPath”. Must be one of [“validatesXPath”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_assertion_x_path_target¶

class SyntheticsAssertionXPathTarget(*args, **kwargs)¶

Bases: ModelNormal

An assertion for the validatesXPath operator.

Parameters:

operator (SyntheticsAssertionXPathOperator) – Assertion operator to apply.
_property (str, optional) – The associated assertion property.
target (SyntheticsAssertionXPathTargetTarget, optional) – Composed target for validatesXPath operator.
type (SyntheticsAssertionType) – Type of the assertion.

synthetics_assertion_x_path_target_target¶

class SyntheticsAssertionXPathTargetTarget(*args, **kwargs)¶

Bases: ModelNormal

Composed target for validatesXPath operator.

Parameters:

operator (str, optional) – The specific operator to use on the path.
target_value (bool, date, datetime, dict, float, int, list, str, UUID, none_type, optional) – The path target value to compare to.
x_path (str, optional) – The X path to assert.

synthetics_basic_auth¶

class SyntheticsBasicAuth(*args, **kwargs)¶

Bases: ModelComposed

Object to handle basic authentication when performing the test.

Parameters:

password (str) – Password to use for the basic authentication.
type (SyntheticsBasicAuthWebType, optional) – The type of basic authentication to use when performing the test.
username (str) – Username to use for the basic authentication.
access_key (str) – Access key for the SIGV4 authentication.
region (str, optional) – Region for the SIGV4 authentication.
secret_key (str) – Secret key for the SIGV4 authentication.
service_name (str, optional) – Service name for the SIGV4 authentication.
session_token (str, optional) – Session token for the SIGV4 authentication.
domain (str, optional) – Domain for the authentication to use when performing the test.
workstation (str, optional) – Workstation for the authentication to use when performing the test.
access_token_url (str) – Access token URL to use when performing the authentication.
audience (str, optional) – Audience to use when performing the authentication.
client_id (str) – Client ID to use when performing the authentication.
client_secret (str) – Client secret to use when performing the authentication.
resource (str, optional) – Resource to use when performing the authentication.
scope (str, optional) – Scope to use when performing the authentication.
token_api_authentication (SyntheticsBasicAuthOauthTokenApiAuthentication) – Type of token to use when performing the authentication.

synthetics_basic_auth_digest¶

class SyntheticsBasicAuthDigest(*args, **kwargs)¶

Bases: ModelNormal

Object to handle digest authentication when performing the test.

Parameters:

password (str) – Password to use for the digest authentication.
type (SyntheticsBasicAuthDigestType, optional) – The type of basic authentication to use when performing the test.
username (str) – Username to use for the digest authentication.

synthetics_basic_auth_digest_type¶

class SyntheticsBasicAuthDigestType(*args, **kwargs)¶

Bases: ModelSimple

The type of basic authentication to use when performing the test.

Parameters:

value (str) – If omitted defaults to “digest”. Must be one of [“digest”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_basic_auth_ntlm¶

class SyntheticsBasicAuthNTLM(*args, **kwargs)¶

Bases: ModelNormal

Object to handle NTLM authentication when performing the test.

Parameters:

domain (str, optional) – Domain for the authentication to use when performing the test.
password (str, optional) – Password for the authentication to use when performing the test.
type (SyntheticsBasicAuthNTLMType) – The type of authentication to use when performing the test.
username (str, optional) – Username for the authentication to use when performing the test.
workstation (str, optional) – Workstation for the authentication to use when performing the test.

synthetics_basic_auth_ntlm_type¶

class SyntheticsBasicAuthNTLMType(*args, **kwargs)¶

Bases: ModelSimple

The type of authentication to use when performing the test.

Parameters:

value (str) – If omitted defaults to “ntlm”. Must be one of [“ntlm”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_basic_auth_oauth_client¶

class SyntheticsBasicAuthOauthClient(*args, **kwargs)¶

Bases: ModelNormal

Object to handle oauth client authentication when performing the test.

Parameters:

access_token_url (str) – Access token URL to use when performing the authentication.
audience (str, optional) – Audience to use when performing the authentication.
client_id (str) – Client ID to use when performing the authentication.
client_secret (str) – Client secret to use when performing the authentication.
resource (str, optional) – Resource to use when performing the authentication.
scope (str, optional) – Scope to use when performing the authentication.
token_api_authentication (SyntheticsBasicAuthOauthTokenApiAuthentication) – Type of token to use when performing the authentication.
type (SyntheticsBasicAuthOauthClientType, optional) – The type of basic authentication to use when performing the test.

synthetics_basic_auth_oauth_client_type¶

class SyntheticsBasicAuthOauthClientType(*args, **kwargs)¶

Bases: ModelSimple

The type of basic authentication to use when performing the test.

Parameters:

value (str) – If omitted defaults to “oauth-client”. Must be one of [“oauth-client”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_basic_auth_oauth_rop¶

class SyntheticsBasicAuthOauthROP(*args, **kwargs)¶

Bases: ModelNormal

Object to handle oauth rop authentication when performing the test.

Parameters:

access_token_url (str) – Access token URL to use when performing the authentication.
audience (str, optional) – Audience to use when performing the authentication.
client_id (str, optional) – Client ID to use when performing the authentication.
client_secret (str, optional) – Client secret to use when performing the authentication.
password (str) – Password to use when performing the authentication.
resource (str, optional) – Resource to use when performing the authentication.
scope (str, optional) – Scope to use when performing the authentication.
token_api_authentication (SyntheticsBasicAuthOauthTokenApiAuthentication) – Type of token to use when performing the authentication.
type (SyntheticsBasicAuthOauthROPType, optional) – The type of basic authentication to use when performing the test.
username (str) – Username to use when performing the authentication.

synthetics_basic_auth_oauth_rop_type¶

class SyntheticsBasicAuthOauthROPType(*args, **kwargs)¶

Bases: ModelSimple

The type of basic authentication to use when performing the test.

Parameters:

value (str) – If omitted defaults to “oauth-rop”. Must be one of [“oauth-rop”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_basic_auth_oauth_token_api_authentication¶

class SyntheticsBasicAuthOauthTokenApiAuthentication(*args, **kwargs)¶

Bases: ModelSimple

Type of token to use when performing the authentication.

Parameters:

value (str) – Must be one of [“header”, “body”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_basic_auth_sigv4¶

class SyntheticsBasicAuthSigv4(*args, **kwargs)¶

Bases: ModelNormal

Object to handle SIGV4 authentication when performing the test.

Parameters:

access_key (str) – Access key for the SIGV4 authentication.
region (str, optional) – Region for the SIGV4 authentication.
secret_key (str) – Secret key for the SIGV4 authentication.
service_name (str, optional) – Service name for the SIGV4 authentication.
session_token (str, optional) – Session token for the SIGV4 authentication.
type (SyntheticsBasicAuthSigv4Type) – The type of authentication to use when performing the test.

synthetics_basic_auth_sigv4_type¶

class SyntheticsBasicAuthSigv4Type(*args, **kwargs)¶

Bases: ModelSimple

The type of authentication to use when performing the test.

Parameters:

value (str) – If omitted defaults to “sigv4”. Must be one of [“sigv4”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_basic_auth_web¶

class SyntheticsBasicAuthWeb(*args, **kwargs)¶

Bases: ModelNormal

Object to handle basic authentication when performing the test.

Parameters:

password (str) – Password to use for the basic authentication.
type (SyntheticsBasicAuthWebType, optional) – The type of basic authentication to use when performing the test.
username (str) – Username to use for the basic authentication.

synthetics_basic_auth_web_type¶

class SyntheticsBasicAuthWebType(*args, **kwargs)¶

Bases: ModelSimple

The type of basic authentication to use when performing the test.

Parameters:

value (str) – If omitted defaults to “web”. Must be one of [“web”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_batch_details¶

class SyntheticsBatchDetails(*args, **kwargs)¶

Bases: ModelNormal

Details about a batch response.

Parameters:: data (SyntheticsBatchDetailsData, optional) – Wrapper object that contains the details of a batch.

synthetics_batch_details_data¶

class SyntheticsBatchDetailsData(*args, **kwargs)¶

Bases: ModelNormal

Wrapper object that contains the details of a batch.

Parameters:

metadata (SyntheticsCIBatchMetadata, optional) – Metadata for the Synthetic tests run.
results ([SyntheticsBatchResult], optional) – List of results for the batch.
status (SyntheticsStatus, optional) – Determines whether or not the batch has passed, failed, or is in progress.

synthetics_batch_result¶

class SyntheticsBatchResult(*args, **kwargs)¶

Bases: ModelNormal

Object with the results of a Synthetic batch.

Parameters:

device (SyntheticsDeviceID, optional) – The device ID.
duration (float, optional) – Total duration in millisecond of the test.
execution_rule (SyntheticsTestExecutionRule, optional) – Execution rule for a Synthetic test.
location (str, optional) – Name of the location.
result_id (str, optional) – The ID of the result to get.
retries (float, optional) – Number of times this result has been retried.
status (SyntheticsStatus, optional) – Determines whether or not the batch has passed, failed, or is in progress.
test_name (str, optional) – Name of the test.
test_public_id (str, optional) – The public ID of the Synthetic test.
test_type (SyntheticsTestDetailsType, optional) – Type of the Synthetic test, either api or browser.

synthetics_browser_error¶

class SyntheticsBrowserError(*args, **kwargs)¶

Bases: ModelNormal

Error response object for a browser test.

Parameters:

description (str) – Description of the error.
name (str) – Name of the error.
status (int, optional) – Status Code of the error.
type (SyntheticsBrowserErrorType) – Error type returned by a browser test.

synthetics_browser_error_type¶

class SyntheticsBrowserErrorType(*args, **kwargs)¶

Bases: ModelSimple

Error type returned by a browser test.

Parameters:

value (str) – Must be one of [“network”, “js”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_browser_test¶

class SyntheticsBrowserTest(*args, **kwargs)¶

Bases: ModelNormal

Object containing details about a Synthetic browser test.

Parameters:

config (SyntheticsBrowserTestConfig) – Configuration object for a Synthetic browser test.
locations ([str]) – Array of locations used to run the test.
message (str) – Notification message associated with the test. Message can either be text or an empty string.
monitor_id (int, optional) – The associated monitor ID.
name (str) – Name of the test.
options (SyntheticsTestOptions) – Object describing the extra options for a Synthetic test.
public_id (str, optional) – The public ID of the test.
status (SyntheticsTestPauseStatus, optional) – Define whether you want to start ( live ) or pause ( paused ) a Synthetic test.
steps ([SyntheticsStep], optional) – Array of steps for the test.
tags ([str], optional) – Array of tags attached to the test.
type (SyntheticsBrowserTestType) – Type of the Synthetic test, browser.

synthetics_browser_test_config¶

class SyntheticsBrowserTestConfig(*args, **kwargs)¶

Bases: ModelNormal

Configuration object for a Synthetic browser test.

Parameters:

assertions ([SyntheticsAssertion]) – Array of assertions used for the test.
config_variables ([SyntheticsConfigVariable], optional) – Array of variables used for the test.
request (SyntheticsTestRequest) – Object describing the Synthetic test request.
set_cookie (str, optional) – Cookies to be used for the request, using the Set-Cookie syntax.
variables ([SyntheticsBrowserVariable], optional) – Array of variables used for the test steps.

synthetics_browser_test_failure_code¶

class SyntheticsBrowserTestFailureCode(*args, **kwargs)¶

Bases: ModelSimple

Error code that can be returned by a Synthetic test.

Parameters:

value (str) – Must be one of [“API_REQUEST_FAILURE”, “ASSERTION_FAILURE”, “DOWNLOAD_FILE_TOO_LARGE”, “ELEMENT_NOT_INTERACTABLE”, “EMAIL_VARIABLE_NOT_DEFINED”, “EVALUATE_JAVASCRIPT”, “EVALUATE_JAVASCRIPT_CONTEXT”, “EXTRACT_VARIABLE”, “FORBIDDEN_URL”, “FRAME_DETACHED”, “INCONSISTENCIES”, “INTERNAL_ERROR”, “INVALID_TYPE_TEXT_DELAY”, “INVALID_URL”, “INVALID_VARIABLE_PATTERN”, “INVISIBLE_ELEMENT”, “LOCATE_ELEMENT”, “NAVIGATE_TO_LINK”, “OPEN_URL”, “PRESS_KEY”, “SERVER_CERTIFICATE”, “SELECT_OPTION”, “STEP_TIMEOUT”, “SUB_TEST_NOT_PASSED”, “TEST_TIMEOUT”, “TOO_MANY_HTTP_REQUESTS”, “UNAVAILABLE_BROWSER”, “UNKNOWN”, “UNSUPPORTED_AUTH_SCHEMA”, “UPLOAD_FILES_ELEMENT_TYPE”, “UPLOAD_FILES_DIALOG”, “UPLOAD_FILES_DYNAMIC_ELEMENT”, “UPLOAD_FILES_NAME”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_browser_test_result_data¶

class SyntheticsBrowserTestResultData(*args, **kwargs)¶

Bases: ModelNormal

Object containing results for your Synthetic browser test.

Parameters:

browser_type (str, optional) – Type of browser device used for the browser test.
browser_version (str, optional) – Browser version used for the browser test.
device (SyntheticsDevice, optional) – Object describing the device used to perform the Synthetic test.
duration (float, optional) – Global duration in second of the browser test.
error (str, optional) – Error returned for the browser test.
failure (SyntheticsBrowserTestResultFailure, optional) – The browser test failure details.
passed (bool, optional) – Whether or not the browser test was conducted.
received_email_count (int, optional) – The amount of email received during the browser test.
start_url (str, optional) – Starting URL for the browser test.
step_details ([SyntheticsStepDetail], optional) – Array containing the different browser test steps.
thumbnails_bucket_key (bool, optional) – Whether or not a thumbnail is associated with the browser test.
time_to_interactive (float, optional) – Time in second to wait before the browser test starts after reaching the start URL.

synthetics_browser_test_result_failure¶

class SyntheticsBrowserTestResultFailure(*args, **kwargs)¶

Bases: ModelNormal

The browser test failure details.

Parameters:

code (SyntheticsBrowserTestFailureCode, optional) – Error code that can be returned by a Synthetic test.
message (str, optional) – The browser test error message.

synthetics_browser_test_result_full¶

class SyntheticsBrowserTestResultFull(*args, **kwargs)¶

Bases: ModelNormal

Object returned describing a browser test result.

Parameters:

check (SyntheticsBrowserTestResultFullCheck, optional) – Object describing the browser test configuration.
check_time (float, optional) – When the browser test was conducted.
check_version (int, optional) – Version of the browser test used.
probe_dc (str, optional) – Location from which the browser test was performed.
result (SyntheticsBrowserTestResultData, optional) – Object containing results for your Synthetic browser test.
result_id (str, optional) – ID of the browser test result.
status (SyntheticsTestMonitorStatus, optional) –
The status of your Synthetic monitor.
- O for not triggered
- 1 for triggered
- 2 for no data

synthetics_browser_test_result_full_check¶

class SyntheticsBrowserTestResultFullCheck(*args, **kwargs)¶

Bases: ModelNormal

Object describing the browser test configuration.

Parameters:: config (SyntheticsTestConfig) – Configuration object for a Synthetic test.

synthetics_browser_test_result_short¶

class SyntheticsBrowserTestResultShort(*args, **kwargs)¶

Bases: ModelNormal

Object with the results of a single Synthetic browser test.

Parameters:

check_time (float, optional) – Last time the browser test was performed.
probe_dc (str, optional) – Location from which the Browser test was performed.
result (SyntheticsBrowserTestResultShortResult, optional) – Object with the result of the last browser test run.
result_id (str, optional) – ID of the browser test result.
status (SyntheticsTestMonitorStatus, optional) –
The status of your Synthetic monitor.
- O for not triggered
- 1 for triggered
- 2 for no data

synthetics_browser_test_result_short_result¶

class SyntheticsBrowserTestResultShortResult(*args, **kwargs)¶

Bases: ModelNormal

Object with the result of the last browser test run.

Parameters:

device (SyntheticsDevice, optional) – Object describing the device used to perform the Synthetic test.
duration (float, optional) – Length in milliseconds of the browser test run.
error_count (int, optional) – Amount of errors collected for a single browser test run.
step_count_completed (int, optional) – Amount of browser test steps completed before failing.
step_count_total (int, optional) – Total amount of browser test steps.

synthetics_browser_test_rum_settings¶

class SyntheticsBrowserTestRumSettings(*args, **kwargs)¶

Bases: ModelNormal

The RUM data collection settings for the Synthetic browser test. Note: There are 3 ways to format RUM settings:

{ isEnabled: false } RUM data is not collected.

{ isEnabled: true } RUM data is collected from the Synthetic test’s default application.

{ isEnabled: true, applicationId: "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx", clientTokenId: 12345 } RUM data is collected using the specified application.

Parameters:

application_id (str, optional) – RUM application ID used to collect RUM data for the browser test.
client_token_id (int, optional) – RUM application API key ID used to collect RUM data for the browser test.
is_enabled (bool) – Determines whether RUM data is collected during test runs.

synthetics_browser_test_type¶

class SyntheticsBrowserTestType(*args, **kwargs)¶

Bases: ModelSimple

Type of the Synthetic test, browser.

Parameters:

value (str) – If omitted defaults to “browser”. Must be one of [“browser”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_browser_variable¶

class SyntheticsBrowserVariable(*args, **kwargs)¶

Bases: ModelNormal

Object defining a variable that can be used in your browser test. See the Recording Steps documentation.

Parameters:

example (str, optional) – Example for the variable.
id (str, optional) – ID for the variable. Global variables require an ID.
name (str) – Name of the variable.
pattern (str, optional) – Pattern of the variable.
secure (bool, optional) – Determines whether or not the browser test variable is obfuscated. Can only be used with browser variables of type text.
type (SyntheticsBrowserVariableType) – Type of browser test variable.

synthetics_browser_variable_type¶

class SyntheticsBrowserVariableType(*args, **kwargs)¶

Bases: ModelSimple

Type of browser test variable.

Parameters:

value (str) – Must be one of [“element”, “email”, “global”, “javascript”, “text”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_check_type¶

class SyntheticsCheckType(*args, **kwargs)¶

Bases: ModelSimple

Type of assertion to apply in an API test.

Parameters:

value (str) – Must be one of [“equals”, “notEquals”, “contains”, “notContains”, “startsWith”, “notStartsWith”, “greater”, “lower”, “greaterEquals”, “lowerEquals”, “matchRegex”, “between”, “isEmpty”, “notIsEmpty”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_ci_batch_metadata¶

class SyntheticsCIBatchMetadata(*args, **kwargs)¶

Bases: ModelNormal

Metadata for the Synthetic tests run.

Parameters:

ci (SyntheticsCIBatchMetadataCI, optional) – Description of the CI provider.
git (SyntheticsCIBatchMetadataGit, optional) – Git information.

synthetics_ci_batch_metadata_ci¶

class SyntheticsCIBatchMetadataCI(*args, **kwargs)¶

Bases: ModelNormal

Description of the CI provider.

Parameters:

pipeline (SyntheticsCIBatchMetadataPipeline, optional) – Description of the CI pipeline.
provider (SyntheticsCIBatchMetadataProvider, optional) – Description of the CI provider.

synthetics_ci_batch_metadata_git¶

class SyntheticsCIBatchMetadataGit(*args, **kwargs)¶

Bases: ModelNormal

Git information.

Parameters:

branch (str, optional) – Branch name.
commit_sha (str, optional) – The commit SHA.

synthetics_ci_batch_metadata_pipeline¶

class SyntheticsCIBatchMetadataPipeline(*args, **kwargs)¶

Bases: ModelNormal

Description of the CI pipeline.

Parameters:: url (str, optional) – URL of the pipeline.

synthetics_ci_batch_metadata_provider¶

class SyntheticsCIBatchMetadataProvider(*args, **kwargs)¶

Bases: ModelNormal

Description of the CI provider.

Parameters:: name (str, optional) – Name of the CI provider.

synthetics_ci_test¶

class SyntheticsCITest(*args, **kwargs)¶

Bases: ModelNormal

Configuration for Continuous Testing.

Parameters:

allow_insecure_certificates (bool, optional) – Disable certificate checks in API tests.
basic_auth (SyntheticsBasicAuth, optional) – Object to handle basic authentication when performing the test.
body (str, optional) – Body to include in the test.
body_type (str, optional) – Type of the data sent in a Synthetic API test.
cookies (str, optional) – Cookies for the request.
device_ids ([SyntheticsDeviceID], optional) – For browser test, array with the different device IDs used to run the test.
follow_redirects (bool, optional) – For API HTTP test, whether or not the test should follow redirects.
headers (SyntheticsTestHeaders, optional) – Headers to include when performing the test.
locations ([str], optional) – Array of locations used to run the test.
metadata (SyntheticsCIBatchMetadata, optional) – Metadata for the Synthetic tests run.
public_id (str) – The public ID of the Synthetic test to trigger.
retry (SyntheticsTestOptionsRetry, optional) – Object describing the retry strategy to apply to a Synthetic test.
start_url (str, optional) – Starting URL for the browser test.
variables ({str: (str,)}, optional) – Variables to replace in the test.

synthetics_ci_test_body¶

class SyntheticsCITestBody(*args, **kwargs)¶

Bases: ModelNormal

Object describing the synthetics tests to trigger.

Parameters:: tests ([SyntheticsCITest], optional) – Individual synthetics test.

synthetics_config_variable¶

class SyntheticsConfigVariable(*args, **kwargs)¶

Bases: ModelNormal

Object defining a variable that can be used in your test configuration.

Parameters:

example (str, optional) – Example for the variable.
id (str, optional) – ID of the variable for global variables.
name (str) – Name of the variable.
pattern (str, optional) – Pattern of the variable.
secure (bool, optional) – Whether the value of this variable will be obfuscated in test results. Only for config variables of type text.
type (SyntheticsConfigVariableType) – Type of the configuration variable.

synthetics_config_variable_type¶

class SyntheticsConfigVariableType(*args, **kwargs)¶

Bases: ModelSimple

Type of the configuration variable.

Parameters:

value (str) – Must be one of [“global”, “text”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_core_web_vitals¶

class SyntheticsCoreWebVitals(*args, **kwargs)¶

Bases: ModelNormal

Core Web Vitals attached to a browser test step.

Parameters:

_cls (float, optional) – Cumulative Layout Shift.
lcp (float, optional) – Largest Contentful Paint in milliseconds.
url (str, optional) – URL attached to the metrics.

synthetics_delete_tests_payload¶

class SyntheticsDeleteTestsPayload(*args, **kwargs)¶

Bases: ModelNormal

A JSON list of the ID or IDs of the Synthetic tests that you want to delete.

Parameters:: public_ids ([str], optional) – An array of Synthetic test IDs you want to delete.

synthetics_delete_tests_response¶

class SyntheticsDeleteTestsResponse(*args, **kwargs)¶

Bases: ModelNormal

Response object for deleting Synthetic tests.

Parameters:: deleted_tests ([SyntheticsDeletedTest], optional) – Array of objects containing a deleted Synthetic test ID with the associated deletion timestamp.

synthetics_deleted_test¶

class SyntheticsDeletedTest(*args, **kwargs)¶

Bases: ModelNormal

Object containing a deleted Synthetic test ID with the associated deletion timestamp.

Parameters:

deleted_at (datetime, optional) – Deletion timestamp of the Synthetic test ID.
public_id (str, optional) – The Synthetic test ID deleted.

synthetics_device¶

class SyntheticsDevice(*args, **kwargs)¶

Bases: ModelNormal

Object describing the device used to perform the Synthetic test.

Parameters:

height (int) – Screen height of the device.
id (SyntheticsDeviceID) – The device ID.
is_mobile (bool, optional) – Whether or not the device is a mobile.
name (str) – The device name.
width (int) – Screen width of the device.

synthetics_device_id¶

class SyntheticsDeviceID(*args, **kwargs)¶

Bases: ModelSimple

The device ID.

Parameters:

value (str) – Must be one of [“laptop_large”, “tablet”, “mobile_small”, “chrome.laptop_large”, “chrome.tablet”, “chrome.mobile_small”, “firefox.laptop_large”, “firefox.tablet”, “firefox.mobile_small”, “edge.laptop_large”, “edge.tablet”, “edge.mobile_small”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_get_api_test_latest_results_response¶

class SyntheticsGetAPITestLatestResultsResponse(*args, **kwargs)¶

Bases: ModelNormal

Object with the latest Synthetic API test run.

Parameters:

last_timestamp_fetched (int, optional) – Timestamp of the latest API test run.
results ([SyntheticsAPITestResultShort], optional) – Result of the latest API test run.

synthetics_get_browser_test_latest_results_response¶

class SyntheticsGetBrowserTestLatestResultsResponse(*args, **kwargs)¶

Bases: ModelNormal

Object with the latest Synthetic browser test run.

Parameters:

last_timestamp_fetched (int, optional) – Timestamp of the latest browser test run.
results ([SyntheticsBrowserTestResultShort], optional) – Result of the latest browser test run.

synthetics_global_variable¶

class SyntheticsGlobalVariable(*args, **kwargs)¶

Bases: ModelNormal

Synthetic global variable.

Parameters:

attributes (SyntheticsGlobalVariableAttributes, optional) – Attributes of the global variable.
description (str) – Description of the global variable.
id (str, optional) – Unique identifier of the global variable.
name (str) – Name of the global variable. Unique across Synthetic global variables.
parse_test_options (SyntheticsGlobalVariableParseTestOptions, optional) – Parser options to use for retrieving a Synthetic global variable from a Synthetic test. Used in conjunction with parse_test_public_id.
parse_test_public_id (str, optional) – A Synthetic test ID to use as a test to generate the variable value.
tags ([str]) – Tags of the global variable.
value (SyntheticsGlobalVariableValue) – Value of the global variable.

synthetics_global_variable_attributes¶

class SyntheticsGlobalVariableAttributes(*args, **kwargs)¶

Bases: ModelNormal

Attributes of the global variable.

Parameters:: restricted_roles (SyntheticsRestrictedRoles, optional) – A list of role identifiers that can be pulled from the Roles API, for restricting read and write access.

synthetics_global_variable_options¶

class SyntheticsGlobalVariableOptions(*args, **kwargs)¶

Bases: ModelNormal

Options for the Global Variable for MFA.

Parameters:: totp_parameters (SyntheticsGlobalVariableTOTPParameters, optional) – Parameters for the TOTP/MFA variable

synthetics_global_variable_parse_test_options¶

class SyntheticsGlobalVariableParseTestOptions(*args, **kwargs)¶

Bases: ModelNormal

Parser options to use for retrieving a Synthetic global variable from a Synthetic test. Used in conjunction with parse_test_public_id.

Parameters:

field (str, optional) – When type is http_header , name of the header to use to extract the value.
local_variable_name (str, optional) – When type is local_variable , name of the local variable to use to extract the value.
parser (SyntheticsVariableParser, optional) – Details of the parser to use for the global variable.
type (SyntheticsGlobalVariableParseTestOptionsType) – Property of the Synthetic Test Response to use for a Synthetic global variable.

synthetics_global_variable_parse_test_options_type¶

class SyntheticsGlobalVariableParseTestOptionsType(*args, **kwargs)¶

Bases: ModelSimple

Property of the Synthetic Test Response to use for a Synthetic global variable.

Parameters:

value (str) – Must be one of [“http_body”, “http_header”, “local_variable”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_global_variable_parser_type¶

class SyntheticsGlobalVariableParserType(*args, **kwargs)¶

Bases: ModelSimple

Type of parser for a Synthetic global variable from a synthetics test.

Parameters:

value (str) – Must be one of [“raw”, “json_path”, “regex”, “x_path”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_global_variable_totp_parameters¶

class SyntheticsGlobalVariableTOTPParameters(*args, **kwargs)¶

Bases: ModelNormal

Parameters for the TOTP/MFA variable

Parameters:

digits (int, optional) – Number of digits for the OTP code.
refresh_interval (int, optional) – Interval for which to refresh the token (in seconds).

synthetics_global_variable_value¶

class SyntheticsGlobalVariableValue(*args, **kwargs)¶

Bases: ModelNormal

Value of the global variable.

Parameters:

options (SyntheticsGlobalVariableOptions, optional) – Options for the Global Variable for MFA.
secure (bool, optional) – Determines if the value of the variable is hidden.
value (str, optional) – Value of the global variable. When reading a global variable, the value will not be present if the variable is hidden with the secure property.

synthetics_list_global_variables_response¶

class SyntheticsListGlobalVariablesResponse(*args, **kwargs)¶

Bases: ModelNormal

Object containing an array of Synthetic global variables.

Parameters:: variables ([SyntheticsGlobalVariable], optional) – Array of Synthetic global variables.

synthetics_list_tests_response¶

class SyntheticsListTestsResponse(*args, **kwargs)¶

Bases: ModelNormal

Object containing an array of Synthetic tests configuration.

Parameters:: tests ([SyntheticsTestDetails], optional) – Array of Synthetic tests configuration.

synthetics_location¶

class SyntheticsLocation(*args, **kwargs)¶

Bases: ModelNormal

Synthetic location that can be used when creating or editing a test.

Parameters:

id (str, optional) – Unique identifier of the location.
name (str, optional) – Name of the location.

synthetics_locations¶

class SyntheticsLocations(*args, **kwargs)¶

Bases: ModelNormal

List of Synthetic locations.

Parameters:: locations ([SyntheticsLocation], optional) – List of Synthetic locations.

synthetics_parsing_options¶

class SyntheticsParsingOptions(*args, **kwargs)¶

Bases: ModelNormal

Parsing options for variables to extract.

Parameters:

field (str, optional) – When type is http_header , name of the header to use to extract the value.
name (str, optional) – Name of the variable to extract.
parser (SyntheticsVariableParser, optional) – Details of the parser to use for the global variable.
secure (bool, optional) – Determines whether or not the extracted value will be obfuscated.
type (SyntheticsGlobalVariableParseTestOptionsType, optional) – Property of the Synthetic Test Response to use for a Synthetic global variable.

synthetics_patch_test_body¶

class SyntheticsPatchTestBody(*args, **kwargs)¶

Bases: ModelNormal

Wrapper around an array of JSON Patch operations to perform on the test

Parameters:

data ([SyntheticsPatchTestOperation], optional) –

Array of JSON Patch operations to perform on the test

synthetics_patch_test_operation¶

class SyntheticsPatchTestOperation(*args, **kwargs)¶

Bases: ModelNormal

A single JSON Patch operation to perform on the test

Parameters:

op (SyntheticsPatchTestOperationName, optional) – The operation to perform
path (str, optional) – The path to the value to modify
value (bool, date, datetime, dict, float, int, list, str, UUID, none_type, optional) –
A value to use in a JSON Patch operation

synthetics_patch_test_operation_name¶

class SyntheticsPatchTestOperationName(*args, **kwargs)¶

Bases: ModelSimple

The operation to perform

Parameters:

value (str) – Must be one of [“add”, “remove”, “replace”, “move”, “copy”, “test”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_playing_tab¶

class SyntheticsPlayingTab(*args, **kwargs)¶

Bases: ModelSimple

Navigate between different tabs for your browser test.

Parameters:

value (int) – Must be one of [-1, 0, 1, 2, 3].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_private_location¶

class SyntheticsPrivateLocation(*args, **kwargs)¶

Bases: ModelNormal

Object containing information about the private location to create.

Parameters:

description (str) – Description of the private location.
id (str, optional) – Unique identifier of the private location.
metadata (SyntheticsPrivateLocationMetadata, optional) – Object containing metadata about the private location.
name (str) – Name of the private location.
secrets (SyntheticsPrivateLocationSecrets, optional) – Secrets for the private location. Only present in the response when creating the private location.
tags ([str]) – Array of tags attached to the private location.

synthetics_private_location_creation_response¶

class SyntheticsPrivateLocationCreationResponse(*args, **kwargs)¶

Bases: ModelNormal

Object that contains the new private location, the public key for result encryption, and the configuration skeleton.

Parameters:

config (dict, optional) – Configuration skeleton for the private location. See installation instructions of the private location on how to use this configuration.
private_location (SyntheticsPrivateLocation, optional) – Object containing information about the private location to create.
result_encryption (SyntheticsPrivateLocationCreationResponseResultEncryption, optional) – Public key for the result encryption.

synthetics_private_location_creation_response_result_encryption¶

class SyntheticsPrivateLocationCreationResponseResultEncryption(*args, **kwargs)¶

Bases: ModelNormal

Public key for the result encryption.

Parameters:

id (str, optional) – Fingerprint for the encryption key.
key (str, optional) – Public key for result encryption.

synthetics_private_location_metadata¶

class SyntheticsPrivateLocationMetadata(*args, **kwargs)¶

Bases: ModelNormal

Object containing metadata about the private location.

Parameters:: restricted_roles (SyntheticsRestrictedRoles, optional) – A list of role identifiers that can be pulled from the Roles API, for restricting read and write access.

synthetics_private_location_secrets¶

class SyntheticsPrivateLocationSecrets(*args, **kwargs)¶

Bases: ModelNormal

Secrets for the private location. Only present in the response when creating the private location.

Parameters:

authentication (SyntheticsPrivateLocationSecretsAuthentication, optional) – Authentication part of the secrets.
config_decryption (SyntheticsPrivateLocationSecretsConfigDecryption, optional) – Private key for the private location.

synthetics_private_location_secrets_authentication¶

class SyntheticsPrivateLocationSecretsAuthentication(*args, **kwargs)¶

Bases: ModelNormal

Authentication part of the secrets.

Parameters:

id (str, optional) – Access key for the private location.
key (str, optional) – Secret access key for the private location.

synthetics_private_location_secrets_config_decryption¶

class SyntheticsPrivateLocationSecretsConfigDecryption(*args, **kwargs)¶

Bases: ModelNormal

Private key for the private location.

Parameters:: key (str, optional) – Private key for the private location.

synthetics_restricted_roles¶

class SyntheticsRestrictedRoles(*args, **kwargs)¶

Bases: ModelSimple

A list of role identifiers that can be pulled from the Roles API, for restricting read and write access.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_ssl_certificate¶

class SyntheticsSSLCertificate(*args, **kwargs)¶

Bases: ModelNormal

Object describing the SSL certificate used for a Synthetic test.

Parameters:

cipher (str, optional) – Cipher used for the connection.
exponent (float, optional) – Exponent associated to the certificate.
ext_key_usage ([str], optional) – Array of extensions and details used for the certificate.
fingerprint (str, optional) – MD5 digest of the DER-encoded Certificate information.
fingerprint256 (str, optional) – SHA-1 digest of the DER-encoded Certificate information.
issuer (SyntheticsSSLCertificateIssuer, optional) – Object describing the issuer of a SSL certificate.
modulus (str, optional) – Modulus associated to the SSL certificate private key.
protocol (str, optional) – TLS protocol used for the test.
serial_number (str, optional) – Serial Number assigned by Symantec to the SSL certificate.
subject (SyntheticsSSLCertificateSubject, optional) – Object describing the SSL certificate used for the test.
valid_from (datetime, optional) – Date from which the SSL certificate is valid.
valid_to (datetime, optional) – Date until which the SSL certificate is valid.

synthetics_ssl_certificate_issuer¶

class SyntheticsSSLCertificateIssuer(*args, **kwargs)¶

Bases: ModelNormal

Object describing the issuer of a SSL certificate.

Parameters:

c (str, optional) – Country Name that issued the certificate.
cn (str, optional) – Common Name that issued certificate.
l (str, optional) – Locality that issued the certificate.
o (str, optional) – Organization that issued the certificate.
ou (str, optional) – Organizational Unit that issued the certificate.
st (str, optional) – State Or Province Name that issued the certificate.

synthetics_ssl_certificate_subject¶

class SyntheticsSSLCertificateSubject(*args, **kwargs)¶

Bases: ModelNormal

Object describing the SSL certificate used for the test.

Parameters:

c (str, optional) – Country Name associated with the certificate.
cn (str, optional) – Common Name that associated with the certificate.
l (str, optional) – Locality associated with the certificate.
o (str, optional) – Organization associated with the certificate.
ou (str, optional) – Organizational Unit associated with the certificate.
st (str, optional) – State Or Province Name associated with the certificate.
alt_name (str, optional) – Subject Alternative Name associated with the certificate.

synthetics_status¶

class SyntheticsStatus(*args, **kwargs)¶

Bases: ModelSimple

Determines whether or not the batch has passed, failed, or is in progress.

Parameters:

value (str) – Must be one of [“passed”, “skipped”, “failed”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_step¶

class SyntheticsStep(*args, **kwargs)¶

Bases: ModelNormal

The steps used in a Synthetic browser test.

Parameters:

allow_failure (bool, optional) – A boolean set to allow this step to fail.
is_critical (bool, optional) – A boolean to use in addition to allowFailure to determine if the test should be marked as failed when the step fails.
name (str, optional) – The name of the step.
no_screenshot (bool, optional) – A boolean set to not take a screenshot for the step.
params (dict, optional) – The parameters of the step.
timeout (int, optional) – The time before declaring a step failed.
type (SyntheticsStepType, optional) – Step type used in your Synthetic test.

synthetics_step_detail¶

class SyntheticsStepDetail(*args, **kwargs)¶

Bases: ModelNormal

Object describing a step for a Synthetic test.

Parameters:

browser_errors ([SyntheticsBrowserError], optional) – Array of errors collected for a browser test.
check_type (SyntheticsCheckType, optional) – Type of assertion to apply in an API test.
description (str, optional) – Description of the test.
duration (float, optional) – Total duration in millisecond of the test.
error (str, optional) – Error returned by the test.
playing_tab (SyntheticsPlayingTab, optional) – Navigate between different tabs for your browser test.
screenshot_bucket_key (bool, optional) – Whether or not screenshots where collected by the test.
skipped (bool, optional) – Whether or not to skip this step.
snapshot_bucket_key (bool, optional) – Whether or not snapshots where collected by the test.
step_id (int, optional) – The step ID.
sub_test_step_details ([SyntheticsStepDetail], optional) – If this step includes a sub-test. Subtests documentation.
time_to_interactive (float, optional) – Time before starting the step.
type (SyntheticsStepType, optional) – Step type used in your Synthetic test.
url (str, optional) – URL to perform the step against.
value (bool, date, datetime, dict, float, int, list, str, UUID, none_type, optional) – Value for the step.
vitals_metrics ([SyntheticsCoreWebVitals], optional) – Array of Core Web Vitals metrics for the step.
warnings ([SyntheticsStepDetailWarning], optional) – Warning collected that didn’t failed the step.

synthetics_step_detail_warning¶

class SyntheticsStepDetailWarning(*args, **kwargs)¶

Bases: ModelNormal

Object collecting warnings for a given step.

Parameters:

message (str) – Message for the warning.
type (SyntheticsWarningType) – User locator used.

synthetics_step_type¶

class SyntheticsStepType(*args, **kwargs)¶

Bases: ModelSimple

Step type used in your Synthetic test.

Parameters:

value (str) – Must be one of [“assertCurrentUrl”, “assertElementAttribute”, “assertElementContent”, “assertElementPresent”, “assertEmail”, “assertFileDownload”, “assertFromJavascript”, “assertPageContains”, “assertPageLacks”, “click”, “extractFromJavascript”, “extractVariable”, “goToEmailLink”, “goToUrl”, “goToUrlAndMeasureTti”, “hover”, “playSubTest”, “pressKey”, “refresh”, “runApiTest”, “scroll”, “selectOption”, “typeText”, “uploadFiles”, “wait”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_test_call_type¶

class SyntheticsTestCallType(*args, **kwargs)¶

Bases: ModelSimple

The type of gRPC call to perform.

Parameters:

value (str) – Must be one of [“healthcheck”, “unary”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_test_ci_options¶

class SyntheticsTestCiOptions(*args, **kwargs)¶

Bases: ModelNormal

CI/CD options for a Synthetic test.

Parameters:: execution_rule (SyntheticsTestExecutionRule, optional) – Execution rule for a Synthetic test.

synthetics_test_config¶

class SyntheticsTestConfig(*args, **kwargs)¶

Bases: ModelNormal

Configuration object for a Synthetic test.

Parameters:

assertions ([SyntheticsAssertion], optional) – Array of assertions used for the test. Required for single API tests.
config_variables ([SyntheticsConfigVariable], optional) – Array of variables used for the test.
request (SyntheticsTestRequest, optional) – Object describing the Synthetic test request.
variables ([SyntheticsBrowserVariable], optional) – Browser tests only - array of variables used for the test steps.

synthetics_test_details¶

class SyntheticsTestDetails(*args, **kwargs)¶

Bases: ModelNormal

Object containing details about your Synthetic test.

Parameters:

config (SyntheticsTestConfig, optional) – Configuration object for a Synthetic test.
creator (Creator, optional) – Object describing the creator of the shared element.
locations ([str], optional) – Array of locations used to run the test.
message (str, optional) – Notification message associated with the test.
monitor_id (int, optional) – The associated monitor ID.
name (str, optional) – Name of the test.
options (SyntheticsTestOptions, optional) – Object describing the extra options for a Synthetic test.
public_id (str, optional) – The test public ID.
status (SyntheticsTestPauseStatus, optional) – Define whether you want to start ( live ) or pause ( paused ) a Synthetic test.
steps ([SyntheticsStep], optional) – For browser test, the steps of the test.
subtype (SyntheticsTestDetailsSubType, optional) – The subtype of the Synthetic API test, http , ssl , tcp , dns , icmp , udp , websocket , grpc or multi.
tags ([str], optional) – Array of tags attached to the test.
type (SyntheticsTestDetailsType, optional) – Type of the Synthetic test, either api or browser.

synthetics_test_details_sub_type¶

class SyntheticsTestDetailsSubType(*args, **kwargs)¶

Bases: ModelSimple

The subtype of the Synthetic API test, http, ssl, tcp,: dns, icmp, udp, websocket, grpc or multi.

Parameters:

value (str) – Must be one of [“http”, “ssl”, “tcp”, “dns”, “multi”, “icmp”, “udp”, “websocket”, “grpc”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_test_details_type¶

class SyntheticsTestDetailsType(*args, **kwargs)¶

Bases: ModelSimple

Type of the Synthetic test, either api or browser.

Parameters:

value (str) – Must be one of [“api”, “browser”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_test_execution_rule¶

class SyntheticsTestExecutionRule(*args, **kwargs)¶

Bases: ModelSimple

Execution rule for a Synthetic test.

Parameters:

value (str) – Must be one of [“blocking”, “non_blocking”, “skipped”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_test_headers¶

class SyntheticsTestHeaders(*args, **kwargs)¶

Bases: ModelNormal

Headers to include when performing the test.

synthetics_test_metadata¶

class SyntheticsTestMetadata(*args, **kwargs)¶

Bases: ModelNormal

Metadata to include when performing the gRPC test.

synthetics_test_monitor_status¶

class SyntheticsTestMonitorStatus(*args, **kwargs)¶

Bases: ModelSimple

The status of your Synthetic monitor.

O for not triggered
1 for triggered
2 for no data

Parameters:

value (int) – Must be one of [0, 1, 2].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_test_options¶

class SyntheticsTestOptions(*args, **kwargs)¶

Bases: ModelNormal

Object describing the extra options for a Synthetic test.

Parameters:

accept_self_signed (bool, optional) – For SSL test, whether or not the test should allow self signed certificates.
allow_insecure (bool, optional) – Allows loading insecure content for an HTTP request in an API test.
check_certificate_revocation (bool, optional) – For SSL test, whether or not the test should fail on revoked certificate in stapled OCSP.
ci (SyntheticsTestCiOptions, optional) – CI/CD options for a Synthetic test.
device_ids ([SyntheticsDeviceID], optional) – For browser test, array with the different device IDs used to run the test.
disable_cors (bool, optional) – Whether or not to disable CORS mechanism.
disable_csp (bool, optional) – Disable Content Security Policy for browser tests.
follow_redirects (bool, optional) – For API HTTP test, whether or not the test should follow redirects.
http_version (SyntheticsTestOptionsHTTPVersion, optional) – HTTP version to use for a Synthetic test.
ignore_server_certificate_error (bool, optional) – Ignore server certificate error for browser tests.
initial_navigation_timeout (int, optional) – Timeout before declaring the initial step as failed (in seconds) for browser tests.
min_failure_duration (int, optional) – Minimum amount of time in failure required to trigger an alert.
min_location_failed (int, optional) – Minimum number of locations in failure required to trigger an alert.
monitor_name (str, optional) – The monitor name is used for the alert title as well as for all monitor dashboard widgets and SLOs.
monitor_options (SyntheticsTestOptionsMonitorOptions, optional) – Object containing the options for a Synthetic test as a monitor (for example, renotification).
monitor_priority (int, optional) – Integer from 1 (high) to 5 (low) indicating alert severity.
no_screenshot (bool, optional) – Prevents saving screenshots of the steps.
restricted_roles (SyntheticsRestrictedRoles, optional) – A list of role identifiers that can be pulled from the Roles API, for restricting read and write access.
retry (SyntheticsTestOptionsRetry, optional) – Object describing the retry strategy to apply to a Synthetic test.
rum_settings (SyntheticsBrowserTestRumSettings, optional) –
The RUM data collection settings for the Synthetic browser test. Note: There are 3 ways to format RUM settings:

{ isEnabled: false } RUM data is not collected.

{ isEnabled: true } RUM data is collected from the Synthetic test’s default application.

{ isEnabled: true, applicationId: "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx", clientTokenId: 12345 } RUM data is collected using the specified application.
scheduling (SyntheticsTestOptionsScheduling, optional) – Object containing timeframes and timezone used for advanced scheduling.
tick_every (int, optional) – The frequency at which to run the Synthetic test (in seconds).

synthetics_test_options_monitor_options¶

class SyntheticsTestOptionsMonitorOptions(*args, **kwargs)¶

Bases: ModelNormal

Object containing the options for a Synthetic test as a monitor (for example, renotification).

Parameters:: renotify_interval (int, optional) – Time interval before renotifying if the test is still failing (in minutes).

synthetics_test_options_retry¶

class SyntheticsTestOptionsRetry(*args, **kwargs)¶

Bases: ModelNormal

Object describing the retry strategy to apply to a Synthetic test.

Parameters:

count (int, optional) – Number of times a test needs to be retried before marking a location as failed. Defaults to 0.
interval (float, optional) – Time interval between retries (in milliseconds). Defaults to 300ms.

synthetics_test_options_scheduling¶

class SyntheticsTestOptionsScheduling(*args, **kwargs)¶

Bases: ModelNormal

Object containing timeframes and timezone used for advanced scheduling.

Parameters:

timeframes ([SyntheticsTestOptionsSchedulingTimeframe], optional) – Array containing objects describing the scheduling pattern to apply to each day.
timezone (str, optional) – Timezone in which the timeframe is based.

synthetics_test_options_scheduling_timeframe¶

class SyntheticsTestOptionsSchedulingTimeframe(*args, **kwargs)¶

Bases: ModelNormal

Object describing a timeframe.

Parameters:

day (int, optional) – Number representing the day of the week.
_from (str, optional) – The hour of the day on which scheduling starts.
to (str, optional) – The hour of the day on which scheduling ends.

synthetics_test_pause_status¶

class SyntheticsTestPauseStatus(*args, **kwargs)¶

Bases: ModelSimple

Define whether you want to start (live) or pause (paused) a: Synthetic test.

Parameters:

value (str) – Must be one of [“live”, “paused”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_test_process_status¶

class SyntheticsTestProcessStatus(*args, **kwargs)¶

Bases: ModelSimple

Status of a Synthetic test.

Parameters:

value (str) – Must be one of [“not_scheduled”, “scheduled”, “finished”, “finished_with_error”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_test_request¶

class SyntheticsTestRequest(*args, **kwargs)¶

Bases: ModelNormal

Object describing the Synthetic test request.

Parameters:

allow_insecure (bool, optional) – Allows loading insecure content for an HTTP request in a multistep test step.
basic_auth (SyntheticsBasicAuth, optional) – Object to handle basic authentication when performing the test.
body (str, optional) – Body to include in the test.
body_type (SyntheticsTestRequestBodyType, optional) – Type of the request body.
call_type (SyntheticsTestCallType, optional) – The type of gRPC call to perform.
certificate (SyntheticsTestRequestCertificate, optional) – Client certificate to use when performing the test request.
certificate_domains ([str], optional) – By default, the client certificate is applied on the domain of the starting URL for browser tests. If you want your client certificate to be applied on other domains instead, add them in certificateDomains.
compressed_json_descriptor (str, optional) – A protobuf JSON descriptor that needs to be gzipped first then base64 encoded.
compressed_proto_file (str, optional) – A protobuf file that needs to be gzipped first then base64 encoded.
dns_server (str, optional) – DNS server to use for DNS tests.
dns_server_port (int, optional) – DNS server port to use for DNS tests.
follow_redirects (bool, optional) – Specifies whether or not the request follows redirects.
headers (SyntheticsTestHeaders, optional) – Headers to include when performing the test.
host (str, optional) – Host name to perform the test with.
message (str, optional) – Message to send for UDP or WebSocket tests.
metadata (SyntheticsTestMetadata, optional) – Metadata to include when performing the gRPC test.
method (str, optional) – Either the HTTP method/verb to use or a gRPC method available on the service set in the service field. Required if subtype is HTTP or if subtype is grpc and callType is unary.
no_saving_response_body (bool, optional) – Determines whether or not to save the response body.
number_of_packets (int, optional) – Number of pings to use per test.
persist_cookies (bool, optional) – Persist cookies across redirects.
port (int, optional) – Port to use when performing the test.
proxy (SyntheticsTestRequestProxy, optional) – The proxy to perform the test.
query (dict, optional) – Query to use for the test.
servername (str, optional) – For SSL tests, it specifies on which server you want to initiate the TLS handshake, allowing the server to present one of multiple possible certificates on the same IP address and TCP port number.
service (str, optional) – The gRPC service on which you want to perform the gRPC call.
should_track_hops (bool, optional) – Turns on a traceroute probe to discover all gateways along the path to the host destination.
timeout (float, optional) – Timeout in seconds for the test.
url (str, optional) – URL to perform the test with.

synthetics_test_request_body_type¶

class SyntheticsTestRequestBodyType(*args, **kwargs)¶

Bases: ModelSimple

Type of the request body.

Parameters:

value (str) – Must be one of [“text/plain”, “application/json”, “text/xml”, “text/html”, “application/x-www-form-urlencoded”, “graphql”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

synthetics_test_request_certificate¶

class SyntheticsTestRequestCertificate(*args, **kwargs)¶

Bases: ModelNormal

Client certificate to use when performing the test request.

Parameters:

cert (SyntheticsTestRequestCertificateItem, optional) – Define a request certificate.
key (SyntheticsTestRequestCertificateItem, optional) – Define a request certificate.

synthetics_test_request_certificate_item¶

class SyntheticsTestRequestCertificateItem(*args, **kwargs)¶

Bases: ModelNormal

Define a request certificate.

Parameters:

content (str, optional) – Content of the certificate or key.
filename (str, optional) – File name for the certificate or key.
updated_at (str, optional) – Date of update of the certificate or key, ISO format.

synthetics_test_request_proxy¶

class SyntheticsTestRequestProxy(*args, **kwargs)¶

Bases: ModelNormal

The proxy to perform the test.

Parameters:

headers (SyntheticsTestHeaders, optional) – Headers to include when performing the test.
url (str) – URL of the proxy to perform the test.

synthetics_timing¶

class SyntheticsTiming(*args, **kwargs)¶

Bases: ModelNormal

Object containing all metrics and their values collected for a Synthetic API test. See the Synthetic Monitoring Metrics documentation.

Parameters:

dns (float, optional) – The duration in millisecond of the DNS lookup.
download (float, optional) – The time in millisecond to download the response.
first_byte (float, optional) – The time in millisecond to first byte.
handshake (float, optional) – The duration in millisecond of the TLS handshake.
redirect (float, optional) – The time in millisecond spent during redirections.
ssl (float, optional) – The duration in millisecond of the TLS handshake.
tcp (float, optional) – Time in millisecond to establish the TCP connection.
total (float, optional) – The overall time in millisecond the request took to be processed.
wait (float, optional) – Time spent in millisecond waiting for a response.

synthetics_trigger_body¶

class SyntheticsTriggerBody(*args, **kwargs)¶

Bases: ModelNormal

Object describing the Synthetic tests to trigger.

Parameters:: tests ([SyntheticsTriggerTest]) – Individual Synthetic test.

synthetics_trigger_ci_test_location¶

class SyntheticsTriggerCITestLocation(*args, **kwargs)¶

Bases: ModelNormal

Synthetic location.

Parameters:

id (int, optional) – Unique identifier of the location.
name (str, optional) – Name of the location.

synthetics_trigger_ci_test_run_result¶

class SyntheticsTriggerCITestRunResult(*args, **kwargs)¶

Bases: ModelNormal

Information about a single test run.

Parameters:

device (SyntheticsDeviceID, optional) – The device ID.
location (int, optional) – The location ID of the test run.
public_id (str, optional) – The public ID of the Synthetic test.
result_id (str, optional) – ID of the result.

synthetics_trigger_ci_tests_response¶

class SyntheticsTriggerCITestsResponse(*args, **kwargs)¶

Bases: ModelNormal

Object containing information about the tests triggered.

Parameters:

batch_id (str, none_type, optional) – The public ID of the batch triggered.
locations ([SyntheticsTriggerCITestLocation], optional) – List of Synthetic locations.
results ([SyntheticsTriggerCITestRunResult], optional) – Information about the tests runs.
triggered_check_ids ([str], optional) – The public IDs of the Synthetic test triggered.

synthetics_trigger_test¶

class SyntheticsTriggerTest(*args, **kwargs)¶

Bases: ModelNormal

Test configuration for Synthetics

Parameters:

metadata (SyntheticsCIBatchMetadata, optional) – Metadata for the Synthetic tests run.
public_id (str) – The public ID of the Synthetic test to trigger.

synthetics_update_test_pause_status_payload¶

class SyntheticsUpdateTestPauseStatusPayload(*args, **kwargs)¶

Bases: ModelNormal

Object to start or pause an existing Synthetic test.

Parameters:: new_status (SyntheticsTestPauseStatus, optional) – Define whether you want to start ( live ) or pause ( paused ) a Synthetic test.

synthetics_variable_parser¶

class SyntheticsVariableParser(*args, **kwargs)¶

Bases: ModelNormal

Details of the parser to use for the global variable.

Parameters:

type (SyntheticsGlobalVariableParserType) – Type of parser for a Synthetic global variable from a synthetics test.
value (str, optional) – Regex or JSON path used for the parser. Not used with type raw.

synthetics_warning_type¶

class SyntheticsWarningType(*args, **kwargs)¶

Bases: ModelSimple

User locator used.

Parameters:

value (str) – If omitted defaults to “user_locator”. Must be one of [“user_locator”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

table_widget_cell_display_mode¶

class TableWidgetCellDisplayMode(*args, **kwargs)¶

Bases: ModelSimple

Define a display mode for the table cell.

Parameters:

value (str) – Must be one of [“number”, “bar”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

table_widget_definition¶

class TableWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The table visualization is available on timeboards and screenboards. It displays columns of metrics grouped by tag key.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
has_search_bar (TableWidgetHasSearchBar, optional) – Controls the display of the search bar.
requests ([TableWidgetRequest]) – Widget definition.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of your widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (TableWidgetDefinitionType) – Type of the table widget.

table_widget_definition_type¶

class TableWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the table widget.

Parameters:

value (str) – If omitted defaults to “query_table”. Must be one of [“query_table”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

table_widget_has_search_bar¶

class TableWidgetHasSearchBar(*args, **kwargs)¶

Bases: ModelSimple

Controls the display of the search bar.

Parameters:

value (str) – Must be one of [“always”, “never”, “auto”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

table_widget_request¶

class TableWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated table widget.

Parameters:

aggregator (WidgetAggregator, optional) – Aggregator used for the request.
alias (str, optional) – The column name (defaults to the metric name).
apm_query (LogQueryDefinition, optional) – The log query.
apm_stats_query (ApmStatsQueryDefinition, optional) – The APM stats query for table and distributions widgets.
cell_display_mode ([TableWidgetCellDisplayMode], optional) – A list of display modes for each table cell.
conditional_formats ([WidgetConditionalFormat], optional) – List of conditional formats.
event_query (LogQueryDefinition, optional) – The log query.
formulas ([WidgetFormula], optional) – List of formulas that operate on queries.
limit (int, optional) – For metric queries, the number of lines to show in the table. Only one request should have this property.
log_query (LogQueryDefinition, optional) – The log query.
network_query (LogQueryDefinition, optional) – The log query.
order (WidgetSort, optional) – Widget sorting methods.
process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.
profile_metrics_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – Query definition.
queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.
response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.

tag_to_hosts¶

class TagToHosts(*args, **kwargs)¶

Bases: ModelNormal

In this object, the key is the tag, the value is a list of host names that are reporting that tag.

Parameters:: tags ({str: ([str],)}, optional) – A list of tags to apply to the host.

target_format_type¶

class TargetFormatType(*args, **kwargs)¶

Bases: ModelSimple

If the target_type of the remapper is attribute, try to cast the value to a new specific type.: If the cast is not possible, the original type is kept. string, integer, or double are the possible types. If the target_type is tag, this parameter may not be specified.

Parameters:

value (str) – Must be one of [“auto”, “string”, “integer”, “double”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

timeseries_background¶

class TimeseriesBackground(*args, **kwargs)¶

Bases: ModelNormal

Set a timeseries on the widget background.

Parameters:

type (TimeseriesBackgroundType) – Timeseries is made using an area or bars.
yaxis (WidgetAxis, optional) – Axis controls for the widget.

timeseries_background_type¶

class TimeseriesBackgroundType(*args, **kwargs)¶

Bases: ModelSimple

Timeseries is made using an area or bars.

Parameters:

value (str) – If omitted defaults to “area”. Must be one of [“bars”, “area”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

timeseries_widget_definition¶

class TimeseriesWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The timeseries visualization allows you to display the evolution of one or more metrics, log events, or Indexed Spans over time.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
events ([WidgetEvent], optional) – List of widget events.
legend_columns ([TimeseriesWidgetLegendColumn], optional) – Columns displayed in the legend.
legend_layout (TimeseriesWidgetLegendLayout, optional) – Layout of the legend.
legend_size (str, optional) – Available legend sizes for a widget. Should be one of “0”, “2”, “4”, “8”, “16”, or “auto”.
markers ([WidgetMarker], optional) – List of markers.
requests ([TimeseriesWidgetRequest]) – List of timeseries widget requests.
right_yaxis (WidgetAxis, optional) – Axis controls for the widget.
show_legend (bool, optional) – (screenboard only) Show the legend for this widget.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of your widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (TimeseriesWidgetDefinitionType) – Type of the timeseries widget.
yaxis (WidgetAxis, optional) – Axis controls for the widget.

timeseries_widget_definition_type¶

class TimeseriesWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the timeseries widget.

Parameters:

value (str) – If omitted defaults to “timeseries”. Must be one of [“timeseries”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

timeseries_widget_expression_alias¶

class TimeseriesWidgetExpressionAlias(*args, **kwargs)¶

Bases: ModelNormal

Define an expression alias.

Parameters:

alias_name (str, optional) – Expression alias.
expression (str) – Expression name.

timeseries_widget_legend_column¶

class TimeseriesWidgetLegendColumn(*args, **kwargs)¶

Bases: ModelSimple

Legend column.

Parameters:

value (str) – Must be one of [“value”, “avg”, “sum”, “min”, “max”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

timeseries_widget_legend_layout¶

class TimeseriesWidgetLegendLayout(*args, **kwargs)¶

Bases: ModelSimple

Layout of the legend.

Parameters:

value (str) – Must be one of [“auto”, “horizontal”, “vertical”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

timeseries_widget_request¶

class TimeseriesWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated timeseries widget.

Parameters:

apm_query (LogQueryDefinition, optional) – The log query.
audit_query (LogQueryDefinition, optional) – The log query.
display_type (WidgetDisplayType, optional) – Type of display to use for the request.
event_query (LogQueryDefinition, optional) – The log query.
formulas ([WidgetFormula], optional) – List of formulas that operate on queries.
log_query (LogQueryDefinition, optional) – The log query.
metadata ([TimeseriesWidgetExpressionAlias], optional) – Used to define expression aliases.
network_query (LogQueryDefinition, optional) – The log query.
on_right_yaxis (bool, optional) – Whether or not to display a second y-axis on the right.
process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.
profile_metrics_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – Widget query.
queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.
response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.
style (WidgetRequestStyle, optional) – Define request widget style.

toplist_widget_definition¶

class ToplistWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The top list visualization enables you to display a list of Tag value like hostname or service with the most or least of any metric value, such as highest consumers of CPU, hosts with the least disk space, etc.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
requests ([ToplistWidgetRequest]) – List of top list widget requests.
style (ToplistWidgetStyle, optional) – Style customization for a top list widget.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of your widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (ToplistWidgetDefinitionType) – Type of the top list widget.

toplist_widget_definition_type¶

class ToplistWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the top list widget.

Parameters:

value (str) – If omitted defaults to “toplist”. Must be one of [“toplist”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

toplist_widget_display¶

class ToplistWidgetDisplay(*args, **kwargs)¶

Bases: ModelComposed

Top list widget display options.

Parameters:

legend (ToplistWidgetLegend) – Top list widget stacked legend behavior.
type (ToplistWidgetStackedType) – Top list widget stacked display type.

toplist_widget_flat¶

class ToplistWidgetFlat(*args, **kwargs)¶

Bases: ModelNormal

Top list widget flat display.

Parameters:: type (ToplistWidgetFlatType) – Top list widget flat display type.

toplist_widget_flat_type¶

class ToplistWidgetFlatType(*args, **kwargs)¶

Bases: ModelSimple

Top list widget flat display type.

Parameters:

value (str) – If omitted defaults to “flat”. Must be one of [“flat”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

toplist_widget_legend¶

class ToplistWidgetLegend(*args, **kwargs)¶

Bases: ModelSimple

Top list widget stacked legend behavior.

Parameters:

value (str) – Must be one of [“automatic”, “inline”, “none”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

toplist_widget_request¶

class ToplistWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

Updated top list widget.

Parameters:

apm_query (LogQueryDefinition, optional) – The log query.
audit_query (LogQueryDefinition, optional) – The log query.
conditional_formats ([WidgetConditionalFormat], optional) – List of conditional formats.
event_query (LogQueryDefinition, optional) – The log query.
formulas ([WidgetFormula], optional) – List of formulas that operate on queries.
log_query (LogQueryDefinition, optional) – The log query.
network_query (LogQueryDefinition, optional) – The log query.
process_query (ProcessQueryDefinition, optional) – The process query to use in the widget.
profile_metrics_query (LogQueryDefinition, optional) – The log query.
q (str, optional) – Widget query.
queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.
response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.
rum_query (LogQueryDefinition, optional) – The log query.
security_query (LogQueryDefinition, optional) – The log query.
style (WidgetRequestStyle, optional) – Define request widget style.

toplist_widget_scaling¶

class ToplistWidgetScaling(*args, **kwargs)¶

Bases: ModelSimple

Top list widget scaling definition.

Parameters:

value (str) – Must be one of [“absolute”, “relative”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

toplist_widget_stacked¶

class ToplistWidgetStacked(*args, **kwargs)¶

Bases: ModelNormal

Top list widget stacked display options.

Parameters:

legend (ToplistWidgetLegend) – Top list widget stacked legend behavior.
type (ToplistWidgetStackedType) – Top list widget stacked display type.

toplist_widget_stacked_type¶

class ToplistWidgetStackedType(*args, **kwargs)¶

Bases: ModelSimple

Top list widget stacked display type.

Parameters:

value (str) – If omitted defaults to “stacked”. Must be one of [“stacked”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

toplist_widget_style¶

class ToplistWidgetStyle(*args, **kwargs)¶

Bases: ModelNormal

Style customization for a top list widget.

Parameters:

display (ToplistWidgetDisplay, optional) – Top list widget display options.
scaling (ToplistWidgetScaling, optional) – Top list widget scaling definition.

topology_map_widget_definition¶

class TopologyMapWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

This widget displays a topology of nodes and edges for different data sources. It replaces the service map widget.

Parameters:

custom_links ([WidgetCustomLink], optional) – List of custom links.
requests ([TopologyRequest]) – One or more Topology requests.
title (str, optional) – Title of your widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (TopologyMapWidgetDefinitionType) – Type of the topology map widget.

topology_map_widget_definition_type¶

class TopologyMapWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the topology map widget.

Parameters:

value (str) – If omitted defaults to “topology_map”. Must be one of [“topology_map”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

topology_query¶

class TopologyQuery(*args, **kwargs)¶

Bases: ModelNormal

Query to service-based topology data sources like the service map or data streams.

Parameters:

data_source (TopologyQueryDataSource, optional) – Name of the data source
filters ([str], optional) – Your environment and primary tag (or * if enabled for your account).
service (str, optional) – Name of the service

topology_query_data_source¶

class TopologyQueryDataSource(*args, **kwargs)¶

Bases: ModelSimple

Name of the data source

Parameters:

value (str) – Must be one of [“data_streams”, “service_map”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

topology_request¶

class TopologyRequest(*args, **kwargs)¶

Bases: ModelNormal

Request that will return nodes and edges to be used by topology map.

Parameters:

query (TopologyQuery, optional) – Query to service-based topology data sources like the service map or data streams.
request_type (TopologyRequestType, optional) – Widget request type.

topology_request_type¶

class TopologyRequestType(*args, **kwargs)¶

Bases: ModelSimple

Widget request type.

Parameters:

value (str) – If omitted defaults to “topology”. Must be one of [“topology”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

tree_map_color_by¶

class TreeMapColorBy(*args, **kwargs)¶

Bases: ModelSimple

(deprecated) The attribute formerly used to determine color in the widget.

Parameters:

value (str) – If omitted defaults to “user”. Must be one of [“user”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

tree_map_group_by¶

class TreeMapGroupBy(*args, **kwargs)¶

Bases: ModelSimple

(deprecated) The attribute formerly used to group elements in the widget.

Parameters:

value (str) – Must be one of [“user”, “family”, “process”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

tree_map_size_by¶

class TreeMapSizeBy(*args, **kwargs)¶

Bases: ModelSimple

(deprecated) The attribute formerly used to determine size in the widget.

Parameters:

value (str) – Must be one of [“pct_cpu”, “pct_mem”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

tree_map_widget_definition¶

class TreeMapWidgetDefinition(*args, **kwargs)¶

Bases: ModelNormal

The treemap visualization enables you to display hierarchical and nested data. It is well suited for queries that describe part-whole relationships, such as resource usage by availability zone, data center, or team.

Parameters:

color_by (TreeMapColorBy, optional) – (deprecated) The attribute formerly used to determine color in the widget. Deprecated.
custom_links ([WidgetCustomLink], optional) – List of custom links.
group_by (TreeMapGroupBy, optional) – (deprecated) The attribute formerly used to group elements in the widget. Deprecated.
requests ([TreeMapWidgetRequest]) – List of treemap widget requests.
size_by (TreeMapSizeBy, optional) – (deprecated) The attribute formerly used to determine size in the widget. Deprecated.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – Title of your widget.
type (TreeMapWidgetDefinitionType) – Type of the treemap widget.

tree_map_widget_definition_type¶

class TreeMapWidgetDefinitionType(*args, **kwargs)¶

Bases: ModelSimple

Type of the treemap widget.

Parameters:

value (str) – If omitted defaults to “treemap”. Must be one of [“treemap”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

tree_map_widget_request¶

class TreeMapWidgetRequest(*args, **kwargs)¶

Bases: ModelNormal

An updated treemap widget.

Parameters:

formulas ([WidgetFormula], optional) – List of formulas that operate on queries.
q (str, optional) – The widget metrics query.
queries ([FormulaAndFunctionQueryDefinition], optional) – List of queries that can be returned directly or used in formulas.
response_format (FormulaAndFunctionResponseFormat, optional) – Timeseries, scalar, or event list response. Event list response formats are supported by Geomap widgets.

usage_analyzed_logs_hour¶

class UsageAnalyzedLogsHour(*args, **kwargs)¶

Bases: ModelNormal

The number of analyzed logs for each hour for a given organization.

Parameters:

analyzed_logs (int, none_type, optional) – Contains the number of analyzed logs.
hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_analyzed_logs_response¶

class UsageAnalyzedLogsResponse(*args, **kwargs)¶

Bases: ModelNormal

A response containing the number of analyzed logs for each hour for a given organization.

Parameters:: usage ([UsageAnalyzedLogsHour], optional) – Get hourly usage for analyzed logs.

usage_attribution_aggregates¶

class UsageAttributionAggregates(*args, **kwargs)¶

Bases: ModelSimple

An array of available aggregates.

Parameters:

_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

usage_attribution_aggregates_body¶

class UsageAttributionAggregatesBody(*args, **kwargs)¶

Bases: ModelNormal

The object containing the aggregates.

Parameters:

agg_type (str, optional) – The aggregate type.
field (str, optional) – The field.
value (float, optional) – The value for a given field.

usage_attribution_body¶

class UsageAttributionBody(*args, **kwargs)¶

Bases: ModelNormal

Usage Summary by tag for a given organization.

Parameters:

month (datetime, optional) – Datetime in ISO-8601 format, UTC, precise to month: [YYYY-MM].
org_name (str, optional) – The name of the organization.
public_id (str, optional) – The organization public ID.
tag_config_source (str, optional) – The source of the usage attribution tag configuration and the selected tags in the format <source_org_name>:::<selected tag 1>///<selected tag 2>///<selected tag 3>.
tags (UsageAttributionTagNames, none_type, optional) –
Tag keys and values.

A null value here means that the requested tag breakdown cannot be applied because it does not match the tags configured for usage attribution. In this scenario the API returns the total usage, not broken down by tags.
updated_at (str, optional) – Shows the the most recent hour in the current months for all organizations for which all usages were calculated.
values (UsageAttributionValues, optional) – Fields in Usage Summary by tag(s).

usage_attribution_metadata¶

class UsageAttributionMetadata(*args, **kwargs)¶

Bases: ModelNormal

The object containing document metadata.

Parameters:

aggregates (UsageAttributionAggregates, optional) – An array of available aggregates.
pagination (UsageAttributionPagination, optional) – The metadata for the current pagination.

usage_attribution_pagination¶

class UsageAttributionPagination(*args, **kwargs)¶

Bases: ModelNormal

The metadata for the current pagination.

Parameters:

limit (int, optional) – Maximum amount of records to be returned.
offset (int, optional) – Records to be skipped before beginning to return.
sort_direction (str, optional) – Direction to sort by.
sort_name (str, optional) – Field to sort by.
total_number_of_records (int, optional) – Total number of records.

usage_attribution_response¶

class UsageAttributionResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the Usage Summary by tag(s).

Parameters:

metadata (UsageAttributionMetadata, optional) – The object containing document metadata.
usage ([UsageAttributionBody], optional) – Get usage summary by tag(s).

usage_attribution_sort¶

class UsageAttributionSort(*args, **kwargs)¶

Bases: ModelSimple

The field to sort by.

Parameters:

value (str) – If omitted defaults to “custom_timeseries_usage”. Must be one of [“api_percentage”, “snmp_usage”, “apm_host_usage”, “api_usage”, “appsec_usage”, “appsec_percentage”, “container_usage”, “custom_timeseries_percentage”, “container_percentage”, “apm_host_percentage”, “npm_host_percentage”, “browser_percentage”, “browser_usage”, “infra_host_percentage”, “snmp_percentage”, “npm_host_usage”, “infra_host_usage”, “custom_timeseries_usage”, “lambda_functions_usage”, “lambda_functions_percentage”, “lambda_invocations_usage”, “lambda_invocations_percentage”, “estimated_indexed_logs_usage”, “estimated_indexed_logs_percentage”, “estimated_ingested_logs_usage”, “estimated_ingested_logs_percentage”, “estimated_indexed_spans_usage”, “estimated_indexed_spans_percentage”, “estimated_ingested_spans_usage”, “estimated_ingested_spans_percentage”, “apm_fargate_usage”, “apm_fargate_percentage”, “appsec_fargate_usage”, “appsec_fargate_percentage”, “estimated_rum_usage_attribution_usage”, “estimated_rum_usage_attribution_percentage”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

usage_attribution_supported_metrics¶

class UsageAttributionSupportedMetrics(*args, **kwargs)¶

Bases: ModelSimple

Supported fields for usage attribution requests (valid requests contain one or more metrics, or * for all).

Parameters:

value (str) – Must be one of [“custom_timeseries_usage”, “container_usage”, “snmp_percentage”, “apm_host_usage”, “browser_usage”, “npm_host_percentage”, “infra_host_usage”, “custom_timeseries_percentage”, “container_percentage”, “api_usage”, “apm_host_percentage”, “infra_host_percentage”, “snmp_usage”, “browser_percentage”, “api_percentage”, “npm_host_usage”, “lambda_functions_usage”, “lambda_functions_percentage”, “lambda_invocations_usage”, “lambda_invocations_percentage”, “fargate_usage”, “fargate_percentage”, “profiled_host_usage”, “profiled_host_percentage”, “profiled_container_usage”, “profiled_container_percentage”, “dbm_hosts_usage”, “dbm_hosts_percentage”, “dbm_queries_usage”, “dbm_queries_percentage”, “estimated_indexed_logs_usage”, “estimated_indexed_logs_percentage”, “estimated_ingested_logs_usage”, “estimated_ingested_logs_percentage”, “appsec_usage”, “appsec_percentage”, “estimated_indexed_spans_usage”, “estimated_indexed_spans_percentage”, “estimated_ingested_spans_usage”, “estimated_ingested_spans_percentage”, “apm_fargate_usage”, “apm_fargate_percentage”, “appsec_fargate_usage”, “appsec_fargate_percentage”, “estimated_rum_usage_attribution_usage”, “estimated_rum_usage_attribution_percentage”, “*”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

usage_attribution_tag_names¶

class UsageAttributionTagNames(*args, **kwargs)¶

Bases: ModelNormal

Tag keys and values.

A null value here means that the requested tag breakdown cannot be applied because it does not match the tags configured for usage attribution. In this scenario the API returns the total usage, not broken down by tags.

usage_attribution_values¶

class UsageAttributionValues(*args, **kwargs)¶

Bases: ModelNormal

Fields in Usage Summary by tag(s).

Parameters:

api_percentage (float, optional) – The percentage of synthetic API test usage by tag(s).
api_usage (float, optional) – The synthetic API test usage by tag(s).
apm_fargate_percentage (float, optional) – The percentage of APM ECS Fargate task usage by tag(s).
apm_fargate_usage (float, optional) – The APM ECS Fargate task usage by tag(s).
apm_host_percentage (float, optional) – The percentage of APM host usage by tag(s).
apm_host_usage (float, optional) – The APM host usage by tag(s).
appsec_fargate_percentage (float, optional) – The percentage of Application Security Monitoring ECS Fargate task usage by tag(s).
appsec_fargate_usage (float, optional) – The Application Security Monitoring ECS Fargate task usage by tag(s).
appsec_percentage (float, optional) – The percentage of Application Security Monitoring host usage by tag(s).
appsec_usage (float, optional) – The Application Security Monitoring host usage by tag(s).
browser_percentage (float, optional) – The percentage of synthetic browser test usage by tag(s).
browser_usage (float, optional) – The synthetic browser test usage by tag(s).
container_percentage (float, optional) – The percentage of container usage by tag(s).
container_usage (float, optional) – The container usage by tag(s).
cspm_container_percentage (float, optional) – The percentage of Cloud Security Management Pro container usage by tag(s)
cspm_container_usage (float, optional) – The Cloud Security Management Pro container usage by tag(s)
cspm_host_percentage (float, optional) – The percentage of Cloud Security Management Pro host usage by tag(s)
cspm_host_usage (float, optional) – The Cloud Security Management Pro host usage by tag(s)
custom_timeseries_percentage (float, optional) – The percentage of custom metrics usage by tag(s).
custom_timeseries_usage (float, optional) – The custom metrics usage by tag(s).
cws_container_percentage (float, optional) – The percentage of Cloud Workload Security container usage by tag(s)
cws_container_usage (float, optional) – The Cloud Workload Security container usage by tag(s)
cws_host_percentage (float, optional) – The percentage of Cloud Workload Security host usage by tag(s)
cws_host_usage (float, optional) – The Cloud Workload Security host usage by tag(s)
dbm_hosts_percentage (float, optional) – The percentage of Database Monitoring host usage by tag(s).
dbm_hosts_usage (float, optional) – The Database Monitoring host usage by tag(s).
dbm_queries_percentage (float, optional) – The percentage of Database Monitoring normalized queries usage by tag(s).
dbm_queries_usage (float, optional) – The Database Monitoring normalized queries usage by tag(s).
estimated_indexed_logs_percentage (float, optional) – The percentage of estimated live indexed logs usage by tag(s).
estimated_indexed_logs_usage (float, optional) – The estimated live indexed logs usage by tag(s).
estimated_indexed_spans_percentage (float, optional) – The percentage of estimated indexed spans usage by tag(s).
estimated_indexed_spans_usage (float, optional) – The estimated indexed spans usage by tag(s).
estimated_ingested_logs_percentage (float, optional) – The percentage of estimated live ingested logs usage by tag(s).
estimated_ingested_logs_usage (float, optional) – The estimated live ingested logs usage by tag(s).
estimated_ingested_spans_percentage (float, optional) – The percentage of estimated ingested spans usage by tag(s).
estimated_ingested_spans_usage (float, optional) – The estimated ingested spans usage by tag(s).
estimated_rum_sessions_percentage (float, optional) – The percentage of estimated rum sessions usage by tag(s).
estimated_rum_sessions_usage (float, optional) – The estimated rum sessions usage by tag(s).
infra_host_percentage (float, optional) – The percentage of infrastructure host usage by tag(s).
infra_host_usage (float, optional) – The infrastructure host usage by tag(s).
lambda_functions_percentage (float, optional) – The percentage of Lambda function usage by tag(s).
lambda_functions_usage (float, optional) – The Lambda function usage by tag(s).
lambda_invocations_percentage (float, optional) – The percentage of Lambda invocation usage by tag(s).
lambda_invocations_usage (float, optional) – The Lambda invocation usage by tag(s).
npm_host_percentage (float, optional) – The percentage of network host usage by tag(s).
npm_host_usage (float, optional) – The network host usage by tag(s).
profiled_container_percentage (float, optional) – The percentage of profiled containers usage by tag(s).
profiled_container_usage (float, optional) – The profiled container usage by tag(s).
profiled_hosts_percentage (float, optional) – The percentage of profiled hosts usage by tag(s).
profiled_hosts_usage (float, optional) – The profiled host usage by tag(s).
snmp_percentage (float, optional) – The percentage of network device usage by tag(s).
snmp_usage (float, optional) – The network device usage by tag(s).

usage_audit_logs_hour¶

class UsageAuditLogsHour(*args, **kwargs)¶

Bases: ModelNormal

Audit logs usage for a given organization for a given hour.

Parameters:

hour (datetime, optional) – The hour for the usage.
lines_indexed (int, none_type, optional) – The total number of audit logs lines indexed during a given hour.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_audit_logs_response¶

class UsageAuditLogsResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the audit logs usage for each hour for a given organization.

Parameters:: usage ([UsageAuditLogsHour], optional) – Get hourly usage for audit logs.

usage_billable_summary_body¶

class UsageBillableSummaryBody(*args, **kwargs)¶

Bases: ModelNormal

Response with properties for each aggregated usage type.

Parameters:

account_billable_usage (int, optional) – The total account usage.
elapsed_usage_hours (int, optional) – Elapsed usage hours for some billable product.
first_billable_usage_hour (datetime, optional) – The first billable hour for the org.
last_billable_usage_hour (datetime, optional) – The last billable hour for the org.
org_billable_usage (int, optional) – The number of units used within the billable timeframe.
percentage_in_account (float, optional) – The percentage of account usage the org represents.
usage_unit (str, optional) – Units pertaining to the usage.

usage_billable_summary_hour¶

class UsageBillableSummaryHour(*args, **kwargs)¶

Bases: ModelNormal

Response with monthly summary of data billed by Datadog.

Parameters:

billing_plan (str, optional) – The billing plan.
end_date (datetime, optional) – Shows the last date of usage.
num_orgs (int, optional) – The number of organizations.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.
ratio_in_month (float, optional) – Shows usage aggregation for a billing period.
region (str, optional) – The region of the organization.
start_date (datetime, optional) – Shows the first date of usage.
usage (UsageBillableSummaryKeys, optional) – Response with aggregated usage types.

usage_billable_summary_keys¶

class UsageBillableSummaryKeys(*args, **kwargs)¶

Bases: ModelNormal

Response with aggregated usage types.

Parameters:

apm_fargate_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
apm_fargate_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
apm_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
apm_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
apm_profiler_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
apm_profiler_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
apm_trace_search_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
application_security_fargate_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
application_security_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
application_security_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
ci_pipeline_indexed_spans_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
ci_pipeline_maximum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
ci_pipeline_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
ci_test_indexed_spans_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
ci_testing_maximum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
ci_testing_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
cloud_cost_management_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
cloud_cost_management_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
cspm_container_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
cspm_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
cspm_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
custom_event_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
cws_container_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
cws_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
cws_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
dbm_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
dbm_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
dbm_normalized_queries_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
dbm_normalized_queries_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
fargate_container_apm_and_profiler_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
fargate_container_apm_and_profiler_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
fargate_container_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
fargate_container_profiler_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
fargate_container_profiler_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
fargate_container_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
incident_management_maximum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
incident_management_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
infra_and_apm_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
infra_and_apm_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
infra_container_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
infra_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
infra_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
ingested_spans_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
ingested_timeseries_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
ingested_timeseries_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
iot_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
iot_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
lambda_function_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
lambda_function_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_forwarding_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_15day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_180day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_30day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_360day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_3day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_45day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_60day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_7day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_90day_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_custom_retention_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_indexed_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
logs_ingested_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
network_device_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
network_device_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
npm_flow_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
npm_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
npm_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
observability_pipeline_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
online_archive_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
prof_container_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
prof_host_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
prof_host_top99p (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
rum_lite_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
rum_replay_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
rum_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
rum_units_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
sensitive_data_scanner_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
serverless_apm_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
serverless_infra_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
serverless_infra_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
serverless_invocation_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
siem_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
standard_timeseries_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
synthetics_api_tests_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
synthetics_app_testing_maximum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
synthetics_browser_checks_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
timeseries_average (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.
timeseries_sum (UsageBillableSummaryBody, optional) – Response with properties for each aggregated usage type.

usage_billable_summary_response¶

class UsageBillableSummaryResponse(*args, **kwargs)¶

Bases: ModelNormal

Response with monthly summary of data billed by Datadog.

Parameters:: usage ([UsageBillableSummaryHour], optional) – An array of objects regarding usage of billable summary.

usage_ci_visibility_hour¶

class UsageCIVisibilityHour(*args, **kwargs)¶

Bases: ModelNormal

CI visibility usage in a given hour.

Parameters:

ci_pipeline_indexed_spans (int, none_type, optional) – The number of spans for pipelines in the queried hour.
ci_test_indexed_spans (int, none_type, optional) – The number of spans for tests in the queried hour.
ci_visibility_itr_committers (int, none_type, optional) – Shows the total count of all active Git committers for Intelligent Test Runner in the current month. A committer is active if they commit at least 3 times in a given month.
ci_visibility_pipeline_committers (int, none_type, optional) – Shows the total count of all active Git committers for Pipelines in the current month. A committer is active if they commit at least 3 times in a given month.
ci_visibility_test_committers (int, none_type, optional) – The total count of all active Git committers for tests in the current month. A committer is active if they commit at least 3 times in a given month.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_ci_visibility_response¶

class UsageCIVisibilityResponse(*args, **kwargs)¶

Bases: ModelNormal

CI visibility usage response

Parameters:: usage ([UsageCIVisibilityHour], optional) – Response containing CI visibility usage.

usage_cloud_security_posture_management_hour¶

class UsageCloudSecurityPostureManagementHour(*args, **kwargs)¶

Bases: ModelNormal

Cloud Security Management Pro usage for a given organization for a given hour.

Parameters:

aas_host_count (float, none_type, optional) – The number of Cloud Security Management Pro Azure app services hosts during a given hour.
aws_host_count (float, none_type, optional) – The number of Cloud Security Management Pro AWS hosts during a given hour.
azure_host_count (float, none_type, optional) – The number of Cloud Security Management Pro Azure hosts during a given hour.
compliance_host_count (float, none_type, optional) – The number of Cloud Security Management Pro hosts during a given hour.
container_count (float, none_type, optional) – The total number of Cloud Security Management Pro containers during a given hour.
gcp_host_count (float, none_type, optional) – The number of Cloud Security Management Pro GCP hosts during a given hour.
host_count (float, none_type, optional) – The total number of Cloud Security Management Pro hosts during a given hour.
hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_cloud_security_posture_management_response¶

class UsageCloudSecurityPostureManagementResponse(*args, **kwargs)¶

Bases: ModelNormal

The response containing the Cloud Security Management Pro usage for each hour for a given organization.

Parameters:: usage ([UsageCloudSecurityPostureManagementHour], optional) – Get hourly usage for Cloud Security Management Pro.

usage_custom_reports_attributes¶

class UsageCustomReportsAttributes(*args, **kwargs)¶

Bases: ModelNormal

The response containing attributes for custom reports.

Parameters:

computed_on (str, optional) – The date the specified custom report was computed.
end_date (str, optional) – The ending date of custom report.
size (int, optional) – size
start_date (str, optional) – The starting date of custom report.
tags ([str], optional) – A list of tags to apply to custom reports.

usage_custom_reports_data¶

class UsageCustomReportsData(*args, **kwargs)¶

Bases: ModelNormal

The response containing the date and type for custom reports.

Parameters:

attributes (UsageCustomReportsAttributes, optional) – The response containing attributes for custom reports.
id (str, optional) – The date for specified custom reports.
type (UsageReportsType, optional) – The type of reports.

usage_custom_reports_meta¶

class UsageCustomReportsMeta(*args, **kwargs)¶

Bases: ModelNormal

The object containing document metadata.

Parameters:: page (UsageCustomReportsPage, optional) – The object containing page total count.

usage_custom_reports_page¶

class UsageCustomReportsPage(*args, **kwargs)¶

Bases: ModelNormal

The object containing page total count.

Parameters:: total_count (int, optional) – Total page count.

usage_custom_reports_response¶

class UsageCustomReportsResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing available custom reports.

Parameters:

data ([UsageCustomReportsData], optional) – An array of available custom reports.
meta (UsageCustomReportsMeta, optional) – The object containing document metadata.

usage_cws_hour¶

class UsageCWSHour(*args, **kwargs)¶

Bases: ModelNormal

Cloud Workload Security usage for a given organization for a given hour.

Parameters:

cws_container_count (int, none_type, optional) – The total number of Cloud Workload Security container hours from the start of the given hour’s month until the given hour.
cws_host_count (int, none_type, optional) – The total number of Cloud Workload Security host hours from the start of the given hour’s month until the given hour.
hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_cws_response¶

class UsageCWSResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the Cloud Workload Security usage for each hour for a given organization.

Parameters:: usage ([UsageCWSHour], optional) – Get hourly usage for Cloud Workload Security.

usage_dbm_hour¶

class UsageDBMHour(*args, **kwargs)¶

Bases: ModelNormal

Database Monitoring usage for a given organization for a given hour.

Parameters:

dbm_host_count (int, none_type, optional) – The total number of Database Monitoring host hours from the start of the given hour’s month until the given hour.
dbm_queries_count (int, none_type, optional) – The total number of normalized Database Monitoring queries from the start of the given hour’s month until the given hour.
hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_dbm_response¶

class UsageDBMResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the Database Monitoring usage for each hour for a given organization.

Parameters:: usage ([UsageDBMHour], optional) – Get hourly usage for Database Monitoring

usage_fargate_hour¶

class UsageFargateHour(*args, **kwargs)¶

Bases: ModelNormal

Number of Fargate tasks run and hourly usage.

Parameters:

apm_fargate_count (int, none_type, optional) – The high-water mark of APM ECS Fargate tasks during the given hour.
appsec_fargate_count (int, none_type, optional) – The Application Security Monitoring ECS Fargate tasks during the given hour.
avg_profiled_fargate_tasks (int, none_type, optional) – The average profiled task count for Fargate Profiling.
hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.
tasks_count (int, none_type, optional) – The number of Fargate tasks run.

usage_fargate_response¶

class UsageFargateResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of Fargate tasks run and hourly usage.

Parameters:: usage ([UsageFargateHour], optional) – Array with the number of hourly Fargate tasks recorded for a given organization.

usage_host_hour¶

class UsageHostHour(*args, **kwargs)¶

Bases: ModelNormal

Number of hosts/containers recorded for each hour for a given organization.

Parameters:

agent_host_count (int, none_type, optional) – Contains the total number of infrastructure hosts reporting during a given hour that were running the Datadog Agent.
alibaba_host_count (int, none_type, optional) – Contains the total number of hosts that reported through Alibaba integration (and were NOT running the Datadog Agent).
apm_azure_app_service_host_count (int, none_type, optional) – Contains the total number of Azure App Services hosts using APM.
apm_host_count (int, none_type, optional) – Shows the total number of hosts using APM during the hour, these are counted as billable (except during trial periods).
aws_host_count (int, none_type, optional) – Contains the total number of hosts that reported through the AWS integration (and were NOT running the Datadog Agent).
azure_host_count (int, none_type, optional) – Contains the total number of hosts that reported through Azure integration (and were NOT running the Datadog Agent).
container_count (int, none_type, optional) – Shows the total number of containers reported by the Docker integration during the hour.
gcp_host_count (int, none_type, optional) – Contains the total number of hosts that reported through the Google Cloud integration (and were NOT running the Datadog Agent).
heroku_host_count (int, none_type, optional) – Contains the total number of Heroku dynos reported by the Datadog Agent.
host_count (int, none_type, optional) – Contains the total number of billable infrastructure hosts reporting during a given hour. This is the sum of agent_host_count , aws_host_count , and gcp_host_count.
hour (datetime, none_type, optional) – The hour for the usage.
infra_azure_app_service (int, none_type, optional) – Contains the total number of hosts that reported through the Azure App Services integration (and were NOT running the Datadog Agent).
opentelemetry_apm_host_count (int, none_type, optional) – Contains the total number of hosts using APM reported by Datadog exporter for the OpenTelemetry Collector.
opentelemetry_host_count (int, none_type, optional) – Contains the total number of hosts reported by Datadog exporter for the OpenTelemetry Collector.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.
vsphere_host_count (int, none_type, optional) – Contains the total number of hosts that reported through vSphere integration (and were NOT running the Datadog Agent).

usage_hosts_response¶

class UsageHostsResponse(*args, **kwargs)¶

Bases: ModelNormal

Host usage response.

Parameters:: usage ([UsageHostHour], optional) – An array of objects related to host usage.

usage_incident_management_hour¶

class UsageIncidentManagementHour(*args, **kwargs)¶

Bases: ModelNormal

Incident management usage for a given organization for a given hour.

Parameters:

hour (datetime, optional) – The hour for the usage.
monthly_active_users (int, none_type, optional) – Contains the total number monthly active users from the start of the given hour’s month until the given hour.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_incident_management_response¶

class UsageIncidentManagementResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the incident management usage for each hour for a given organization.

Parameters:: usage ([UsageIncidentManagementHour], optional) – Get hourly usage for incident management.

usage_indexed_spans_hour¶

class UsageIndexedSpansHour(*args, **kwargs)¶

Bases: ModelNormal

The hours of indexed spans usage.

Parameters:

hour (datetime, optional) – The hour for the usage.
indexed_events_count (int, none_type, optional) – Contains the number of spans indexed.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_indexed_spans_response¶

class UsageIndexedSpansResponse(*args, **kwargs)¶

Bases: ModelNormal

A response containing indexed spans usage.

Parameters:: usage ([UsageIndexedSpansHour], optional) – Array with the number of hourly traces indexed for a given organization.

usage_ingested_spans_hour¶

class UsageIngestedSpansHour(*args, **kwargs)¶

Bases: ModelNormal

Ingested spans usage for a given organization for a given hour.

Parameters:

hour (datetime, optional) – The hour for the usage.
ingested_events_bytes (int, none_type, optional) – Contains the total number of bytes ingested for APM spans during a given hour.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_ingested_spans_response¶

class UsageIngestedSpansResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the ingested spans usage for each hour for a given organization.

Parameters:: usage ([UsageIngestedSpansHour], optional) – Get hourly usage for ingested spans.

usage_iot_hour¶

class UsageIoTHour(*args, **kwargs)¶

Bases: ModelNormal

IoT usage for a given organization for a given hour.

Parameters:

hour (datetime, optional) – The hour for the usage.
iot_device_count (int, none_type, optional) – The total number of IoT devices during a given hour.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_iot_response¶

class UsageIoTResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the IoT usage for each hour for a given organization.

Parameters:: usage ([UsageIoTHour], optional) – Get hourly usage for IoT.

usage_lambda_hour¶

class UsageLambdaHour(*args, **kwargs)¶

Bases: ModelNormal

Number of Lambda functions and sum of the invocations of all Lambda functions for each hour for a given organization.

Parameters:

func_count (int, none_type, optional) – Contains the number of different functions for each region and AWS account.
hour (datetime, optional) – The hour for the usage.
invocations_sum (int, none_type, optional) – Contains the sum of invocations of all functions.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_lambda_response¶

class UsageLambdaResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of Lambda functions and sum of the invocations of all Lambda functions for each hour for a given organization.

Parameters:: usage ([UsageLambdaHour], optional) – Get hourly usage for Lambda.

usage_logs_by_index_hour¶

class UsageLogsByIndexHour(*args, **kwargs)¶

Bases: ModelNormal

Number of indexed logs for each hour and index for a given organization.

Parameters:

event_count (int, optional) – The total number of indexed logs for the queried hour.
hour (datetime, optional) – The hour for the usage.
index_id (str, optional) – The index ID for this usage.
index_name (str, optional) – The user specified name for this index ID.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.
retention (int, optional) – The retention period (in days) for this index ID.

usage_logs_by_index_response¶

class UsageLogsByIndexResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of indexed logs for each hour and index for a given organization.

Parameters:: usage ([UsageLogsByIndexHour], optional) – An array of objects regarding hourly usage of logs by index response.

usage_logs_by_retention_hour¶

class UsageLogsByRetentionHour(*args, **kwargs)¶

Bases: ModelNormal

The number of indexed logs for each hour for a given organization broken down by retention period.

Parameters:

indexed_events_count (int, none_type, optional) – Total logs indexed with this retention period during a given hour.
live_indexed_events_count (int, none_type, optional) – Live logs indexed with this retention period during a given hour.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.
rehydrated_indexed_events_count (int, none_type, optional) – Rehydrated logs indexed with this retention period during a given hour.
retention (str, none_type, optional) – The retention period in days or “custom” for all custom retention usage.

usage_logs_by_retention_response¶

class UsageLogsByRetentionResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the indexed logs usage broken down by retention period for an organization during a given hour.

Parameters:: usage ([UsageLogsByRetentionHour], optional) – Get hourly usage for indexed logs by retention period.

usage_logs_hour¶

class UsageLogsHour(*args, **kwargs)¶

Bases: ModelNormal

Hour usage for logs.

Parameters:

billable_ingested_bytes (int, none_type, optional) – Contains the number of billable log bytes ingested.
hour (datetime, optional) – The hour for the usage.
indexed_events_count (int, none_type, optional) – Contains the number of log events indexed.
ingested_events_bytes (int, none_type, optional) – Contains the number of log bytes ingested.
logs_forwarding_events_bytes (int, none_type, optional) – Contains the number of logs forwarded bytes (data available as of April 1st 2023)
logs_live_indexed_count (int, none_type, optional) – Contains the number of live log events indexed (data available as of December 1, 2020).
logs_live_ingested_bytes (int, none_type, optional) – Contains the number of live log bytes ingested (data available as of December 1, 2020).
logs_rehydrated_indexed_count (int, none_type, optional) – Contains the number of rehydrated log events indexed (data available as of December 1, 2020).
logs_rehydrated_ingested_bytes (int, none_type, optional) – Contains the number of rehydrated log bytes ingested (data available as of December 1, 2020).
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_logs_response¶

class UsageLogsResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of logs for each hour.

Parameters:: usage ([UsageLogsHour], optional) – An array of objects regarding hourly usage of logs.

usage_metric_category¶

class UsageMetricCategory(*args, **kwargs)¶

Bases: ModelSimple

Contains the metric category.

Parameters:

value (str) – Must be one of [“standard”, “custom”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

usage_network_flows_hour¶

class UsageNetworkFlowsHour(*args, **kwargs)¶

Bases: ModelNormal

Number of netflow events indexed for each hour for a given organization.

Parameters:

hour (datetime, optional) – The hour for the usage.
indexed_events_count (int, none_type, optional) – Contains the number of netflow events indexed.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_network_flows_response¶

class UsageNetworkFlowsResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of netflow events indexed for each hour for a given organization.

Parameters:: usage ([UsageNetworkFlowsHour], optional) – Get hourly usage for Network Flows.

usage_network_hosts_hour¶

class UsageNetworkHostsHour(*args, **kwargs)¶

Bases: ModelNormal

Number of active NPM hosts for each hour for a given organization.

Parameters:

host_count (int, none_type, optional) – Contains the number of active NPM hosts.
hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_network_hosts_response¶

class UsageNetworkHostsResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of active NPM hosts for each hour for a given organization.

Parameters:: usage ([UsageNetworkHostsHour], optional) – Get hourly usage for NPM hosts.

usage_online_archive_hour¶

class UsageOnlineArchiveHour(*args, **kwargs)¶

Bases: ModelNormal

Online Archive usage in a given hour.

Parameters:

hour (datetime, optional) – The hour for the usage.
online_archive_events_count (int, none_type, optional) – Total count of online archived events within the hour.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_online_archive_response¶

class UsageOnlineArchiveResponse(*args, **kwargs)¶

Bases: ModelNormal

Online Archive usage response.

Parameters:: usage ([UsageOnlineArchiveHour], optional) – Response containing Online Archive usage.

usage_profiling_hour¶

class UsageProfilingHour(*args, **kwargs)¶

Bases: ModelNormal

The number of profiled hosts for each hour for a given organization.

Parameters:

aas_count (int, none_type, optional) – Contains the total number of profiled Azure app services reporting during a given hour.
avg_container_agent_count (int, none_type, optional) – Get average number of container agents for that hour.
host_count (int, none_type, optional) – Contains the total number of profiled hosts reporting during a given hour.
hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_profiling_response¶

class UsageProfilingResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of profiled hosts for each hour for a given organization.

Parameters:: usage ([UsageProfilingHour], optional) – Get hourly usage for profiled hosts.

usage_reports_type¶

class UsageReportsType(*args, **kwargs)¶

Bases: ModelSimple

The type of reports.

Parameters:

value (str) – If omitted defaults to “reports”. Must be one of [“reports”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

usage_rum_sessions_hour¶

class UsageRumSessionsHour(*args, **kwargs)¶

Bases: ModelNormal

Number of RUM Sessions recorded for each hour for a given organization.

Parameters:

hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.
replay_session_count (int, optional) – Contains the number of RUM Replay Sessions (data available beginning November 1, 2021).
session_count (int, none_type, optional) – Contains the number of browser RUM Lite Sessions.
session_count_android (int, none_type, optional) – Contains the number of mobile RUM Sessions on Android (data available beginning December 1, 2020).
session_count_flutter (int, none_type, optional) – Contains the number of mobile RUM Sessions on Flutter (data available beginning March 1, 2023).
session_count_ios (int, none_type, optional) – Contains the number of mobile RUM Sessions on iOS (data available beginning December 1, 2020).
session_count_reactnative (int, none_type, optional) – Contains the number of mobile RUM Sessions on React Native (data available beginning May 1, 2022).

usage_rum_sessions_response¶

class UsageRumSessionsResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of RUM Sessions for each hour for a given organization.

Parameters:: usage ([UsageRumSessionsHour], optional) – Get hourly usage for RUM Sessions.

usage_rum_units_hour¶

class UsageRumUnitsHour(*args, **kwargs)¶

Bases: ModelNormal

Number of RUM Units used for each hour for a given organization (data available as of November 1, 2021).

Parameters:

browser_rum_units (int, none_type, optional) – The number of browser RUM units.
mobile_rum_units (int, none_type, optional) – The number of mobile RUM units.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.
rum_units (int, none_type, optional) – Total RUM units across mobile and browser RUM.

usage_rum_units_response¶

class UsageRumUnitsResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of RUM Units for each hour for a given organization.

Parameters:: usage ([UsageRumUnitsHour], optional) – Get hourly usage for RUM Units.

usage_sds_hour¶

class UsageSDSHour(*args, **kwargs)¶

Bases: ModelNormal

Sensitive Data Scanner usage for a given organization for a given hour.

Parameters:

apm_scanned_bytes (int, none_type, optional) – The total number of bytes scanned of APM usage across all usage types by the Sensitive Data Scanner from the start of the given hour’s month until the given hour.
events_scanned_bytes (int, none_type, optional) – The total number of bytes scanned of Events usage across all usage types by the Sensitive Data Scanner from the start of the given hour’s month until the given hour.
hour (datetime, optional) – The hour for the usage.
logs_scanned_bytes (int, none_type, optional) – The total number of bytes scanned of logs usage by the Sensitive Data Scanner from the start of the given hour’s month until the given hour.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.
rum_scanned_bytes (int, none_type, optional) – The total number of bytes scanned of RUM usage across all usage types by the Sensitive Data Scanner from the start of the given hour’s month until the given hour.
total_scanned_bytes (int, none_type, optional) – The total number of bytes scanned across all usage types by the Sensitive Data Scanner from the start of the given hour’s month until the given hour.

usage_sds_response¶

class UsageSDSResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the Sensitive Data Scanner usage for each hour for a given organization.

Parameters:: usage ([UsageSDSHour], optional) – Get hourly usage for Sensitive Data Scanner.

usage_snmp_hour¶

class UsageSNMPHour(*args, **kwargs)¶

Bases: ModelNormal

The number of SNMP devices for each hour for a given organization.

Parameters:

hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.
snmp_devices (int, none_type, optional) – Contains the number of SNMP devices.

usage_snmp_response¶

class UsageSNMPResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of SNMP devices for each hour for a given organization.

Parameters:: usage ([UsageSNMPHour], optional) – Get hourly usage for SNMP devices.

usage_sort¶

class UsageSort(*args, **kwargs)¶

Bases: ModelSimple

The field to sort by.

Parameters:

value (str) – If omitted defaults to “start_date”. Must be one of [“computed_on”, “size”, “start_date”, “end_date”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

usage_sort_direction¶

class UsageSortDirection(*args, **kwargs)¶

Bases: ModelSimple

The direction to sort by.

Parameters:

value (str) – If omitted defaults to “desc”. Must be one of [“desc”, “asc”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

usage_specified_custom_reports_attributes¶

class UsageSpecifiedCustomReportsAttributes(*args, **kwargs)¶

Bases: ModelNormal

The response containing attributes for specified custom reports.

Parameters:

computed_on (str, optional) – The date the specified custom report was computed.
end_date (str, optional) – The ending date of specified custom report.
location (str, optional) – A downloadable file for the specified custom reporting file.
size (int, optional) – size
start_date (str, optional) – The starting date of specified custom report.
tags ([str], optional) – A list of tags to apply to specified custom reports.

usage_specified_custom_reports_data¶

class UsageSpecifiedCustomReportsData(*args, **kwargs)¶

Bases: ModelNormal

Response containing date and type for specified custom reports.

Parameters:

attributes (UsageSpecifiedCustomReportsAttributes, optional) – The response containing attributes for specified custom reports.
id (str, optional) – The date for specified custom reports.
type (UsageReportsType, optional) – The type of reports.

usage_specified_custom_reports_meta¶

class UsageSpecifiedCustomReportsMeta(*args, **kwargs)¶

Bases: ModelNormal

The object containing document metadata.

Parameters:: page (UsageSpecifiedCustomReportsPage, optional) – The object containing page total count for specified ID.

usage_specified_custom_reports_page¶

class UsageSpecifiedCustomReportsPage(*args, **kwargs)¶

Bases: ModelNormal

The object containing page total count for specified ID.

Parameters:: total_count (int, optional) – Total page count.

usage_specified_custom_reports_response¶

class UsageSpecifiedCustomReportsResponse(*args, **kwargs)¶

Bases: ModelNormal

Returns available specified custom reports.

Parameters:

data (UsageSpecifiedCustomReportsData, optional) – Response containing date and type for specified custom reports.
meta (UsageSpecifiedCustomReportsMeta, optional) – The object containing document metadata.

usage_summary_date¶

class UsageSummaryDate(*args, **kwargs)¶

Bases: ModelNormal

Response with hourly report of all data billed by Datadog all organizations.

Parameters:

agent_host_top99p (int, optional) – Shows the 99th percentile of all agent hosts over all hours in the current date for all organizations.
apm_azure_app_service_host_top99p (int, optional) – Shows the 99th percentile of all Azure app services using APM over all hours in the current date all organizations.
apm_devsecops_host_top99p (int, optional) – Shows the 99th percentile of all APM DevSecOps hosts over all hours in the current date for the given org.
apm_fargate_count_avg (int, optional) – Shows the average of all APM ECS Fargate tasks over all hours in the current date for all organizations.
apm_host_top99p (int, optional) – Shows the 99th percentile of all distinct APM hosts over all hours in the current date for all organizations.
appsec_fargate_count_avg (int, optional) – Shows the average of all Application Security Monitoring ECS Fargate tasks over all hours in the current date for all organizations.
audit_logs_lines_indexed_sum (int, optional) – Shows the sum of audit logs lines indexed over all hours in the current date for all organizations. Deprecated.
audit_trail_enabled_hwm (int, optional) – Shows the number of organizations that had Audit Trail enabled in the current date.
avg_profiled_fargate_tasks (int, optional) – The average profiled task count for Fargate Profiling.
aws_host_top99p (int, optional) – Shows the 99th percentile of all AWS hosts over all hours in the current date for all organizations.
aws_lambda_func_count (int, optional) – Shows the average of the number of functions that executed 1 or more times each hour in the current date for all organizations.
aws_lambda_invocations_sum (int, optional) – Shows the sum of all AWS Lambda invocations over all hours in the current date for all organizations.
azure_app_service_top99p (int, optional) – Shows the 99th percentile of all Azure app services over all hours in the current date for all organizations.
billable_ingested_bytes_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current date for all organizations.
browser_rum_lite_session_count_sum (int, optional) – Shows the sum of all browser lite sessions over all hours in the current date for all organizations.
browser_rum_replay_session_count_sum (int, optional) – Shows the sum of all browser replay sessions over all hours in the current date for all organizations.
browser_rum_units_sum (int, optional) – Shows the sum of all browser RUM units over all hours in the current date for all organizations.
ci_pipeline_indexed_spans_sum (int, optional) – Shows the sum of all CI pipeline indexed spans over all hours in the current month for all organizations.
ci_test_indexed_spans_sum (int, optional) – Shows the sum of all CI test indexed spans over all hours in the current month for all organizations.
ci_visibility_itr_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility intelligent test runner committers over all hours in the current month for all organizations.
ci_visibility_pipeline_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility pipeline committers over all hours in the current month for all organizations.
ci_visibility_test_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility test committers over all hours in the current month for all organizations.
cloud_cost_management_aws_host_count_avg (int, optional) – Host count average of Cloud Cost Management for AWS for the given date and given organization.
cloud_cost_management_azure_host_count_avg (int, optional) – Host count average of Cloud Cost Management for Azure for the given date and given organization.
cloud_cost_management_host_count_avg (int, optional) – Host count average of Cloud Cost Management for all cloud providers for the given date and given organization.
cloud_siem_events_sum (int, optional) – Shows the sum of all Cloud Security Information and Event Management events over all hours in the current date for the given org.
container_avg (int, optional) – Shows the average of all distinct containers over all hours in the current date for all organizations.
container_excl_agent_avg (int, optional) – Shows the average of containers without the Datadog Agent over all hours in the current date for all organizations.
container_hwm (int, optional) – Shows the high-water mark of all distinct containers over all hours in the current date for all organizations.
csm_container_enterprise_compliance_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise compliance containers over all hours in the current date for the given org.
csm_container_enterprise_cws_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise Cloud Workload Security containers over all hours in the current date for the given org.
csm_container_enterprise_total_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise containers over all hours in the current date for the given org.
csm_host_enterprise_aas_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure app services hosts over all hours in the current date for the given org.
csm_host_enterprise_aws_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise AWS hosts over all hours in the current date for the given org.
csm_host_enterprise_azure_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure hosts over all hours in the current date for the given org.
csm_host_enterprise_compliance_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise compliance hosts over all hours in the current date for the given org.
csm_host_enterprise_cws_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Cloud Workload Security hosts over all hours in the current date for the given org.
csm_host_enterprise_gcp_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise GCP hosts over all hours in the current date for the given org.
csm_host_enterprise_total_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise hosts over all hours in the current date for the given org.
cspm_aas_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure app services hosts over all hours in the current date for all organizations.
cspm_aws_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro AWS hosts over all hours in the current date for all organizations.
cspm_azure_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure hosts over all hours in the current date for all organizations.
cspm_container_avg (int, optional) – Shows the average number of Cloud Security Management Pro containers over all hours in the current date for all organizations.
cspm_container_hwm (int, optional) – Shows the high-water mark of Cloud Security Management Pro containers over all hours in the current date for all organizations.
cspm_gcp_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro GCP hosts over all hours in the current date for all organizations.
cspm_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro hosts over all hours in the current date for all organizations.
custom_ts_avg (int, optional) – Shows the average number of distinct custom metrics over all hours in the current date for all organizations.
cws_container_count_avg (int, optional) – Shows the average of all distinct Cloud Workload Security containers over all hours in the current date for all organizations.
cws_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Workload Security hosts over all hours in the current date for all organizations.
date (datetime, optional) – The date for the usage.
dbm_host_top99p (int, optional) – Shows the 99th percentile of all Database Monitoring hosts over all hours in the current date for all organizations.
dbm_queries_count_avg (int, optional) – Shows the average of all normalized Database Monitoring queries over all hours in the current date for all organizations.
fargate_tasks_count_avg (int, optional) – Shows the high-watermark of all Fargate tasks over all hours in the current date for all organizations.
fargate_tasks_count_hwm (int, optional) – Shows the average of all Fargate tasks over all hours in the current date for all organizations.
forwarding_events_bytes_sum (int, optional) – Shows the sum of all log bytes forwarded over all hours in the current date for all organizations.
gcp_host_top99p (int, optional) – Shows the 99th percentile of all GCP hosts over all hours in the current date for all organizations.
heroku_host_top99p (int, optional) – Shows the 99th percentile of all Heroku dynos over all hours in the current date for all organizations.
incident_management_monthly_active_users_hwm (int, optional) – Shows the high-water mark of incident management monthly active users over all hours in the current date for all organizations.
indexed_events_count_sum (int, optional) – Shows the sum of all log events indexed over all hours in the current date for all organizations.
infra_host_top99p (int, optional) – Shows the 99th percentile of all distinct infrastructure hosts over all hours in the current date for all organizations.
ingested_events_bytes_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current date for all organizations.
iot_device_sum (int, optional) – Shows the sum of all IoT devices over all hours in the current date for all organizations.
iot_device_top99p (int, optional) – Shows the 99th percentile of all IoT devices over all hours in the current date all organizations.
mobile_rum_lite_session_count_sum (int, optional) – Shows the sum of all mobile lite sessions over all hours in the current date for all organizations.
mobile_rum_session_count_android_sum (int, optional) – Shows the sum of all mobile RUM Sessions on Android over all hours in the current date for all organizations.
mobile_rum_session_count_flutter_sum (int, optional) – Shows the sum of all mobile RUM Sessions on Flutter over all hours in the current date for all organizations.
mobile_rum_session_count_ios_sum (int, optional) – Shows the sum of all mobile RUM Sessions on iOS over all hours in the current date for all organizations.
mobile_rum_session_count_reactnative_sum (int, optional) – Shows the sum of all mobile RUM Sessions on React Native over all hours in the current date for all organizations.
mobile_rum_session_count_roku_sum (int, optional) – Shows the sum of all mobile RUM Sessions on Roku over all hours in the current date for all organizations.
mobile_rum_session_count_sum (int, optional) – Shows the sum of all mobile RUM Sessions over all hours in the current date for all organizations
mobile_rum_units_sum (int, optional) – Shows the sum of all mobile RUM units over all hours in the current date for all organizations.
ndm_netflow_events_sum (int, optional) – Shows the sum of all Network Device Monitoring NetFlow events over all hours in the current date for the given org.
netflow_indexed_events_count_sum (int, optional) – Shows the sum of all Network flows indexed over all hours in the current date for all organizations.
npm_host_top99p (int, optional) – Shows the 99th percentile of all distinct Networks hosts over all hours in the current date for all organizations.
observability_pipelines_bytes_processed_sum (int, optional) – Sum of all observability pipelines bytes processed over all hours in the current date for the given org.
online_archive_events_count_sum (int, optional) – Sum of all online archived events over all hours in the current date for all organizations.
opentelemetry_apm_host_top99p (int, optional) – Shows the 99th percentile of APM hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for all organizations.
opentelemetry_host_top99p (int, optional) – Shows the 99th percentile of all hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for all organizations.
orgs ([UsageSummaryDateOrg], optional) – Organizations associated with a user.
profiling_aas_count_top99p (int, optional) – Shows the 99th percentile of all profiled Azure app services over all hours in the current date for all organizations.
profiling_host_top99p (int, optional) – Shows the 99th percentile of all profiled hosts over all hours in the current date for all organizations.
rum_browser_and_mobile_session_count (int, optional) – Shows the sum of all mobile sessions and all browser lite and legacy sessions over all hours in the current month for all organizations.
rum_session_count_sum (int, optional) – Shows the sum of all browser RUM Lite Sessions over all hours in the current date for all organizations
rum_total_session_count_sum (int, optional) – Shows the sum of RUM Sessions (browser and mobile) over all hours in the current date for all organizations.
rum_units_sum (int, optional) – Shows the sum of all browser and mobile RUM units over all hours in the current date for all organizations.
sds_apm_scanned_bytes_sum (int, optional) – Sum of all APM bytes scanned with sensitive data scanner over all hours in the current date for all organizations.
sds_events_scanned_bytes_sum (int, optional) – Sum of all event stream events bytes scanned with sensitive data scanner over all hours in the current date for all organizations.
sds_logs_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned of logs usage by the Sensitive Data Scanner over all hours in the current month for all organizations.
sds_rum_scanned_bytes_sum (int, optional) – Sum of all RUM bytes scanned with sensitive data scanner over all hours in the current date for all organizations.
sds_total_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned across all usage types by the Sensitive Data Scanner over all hours in the current month for all organizations.
serverless_apps_azure_count_avg (int, optional) – Shows the average of the number of Serverless Apps for Azure for the given date and given org.
serverless_apps_google_count_avg (int, optional) – Shows the average of the number of Serverless Apps for Google Cloud for the given date and given org.
serverless_apps_total_count_avg (int, optional) – Shows the average of the number of Serverless Apps for Azure and Google Cloud for the given date and given org.
synthetics_browser_check_calls_count_sum (int, optional) – Shows the sum of all Synthetic browser tests over all hours in the current date for all organizations.
synthetics_check_calls_count_sum (int, optional) – Shows the sum of all Synthetic API tests over all hours in the current date for all organizations.
synthetics_mobile_test_runs_sum (int, optional) – Shows the sum of all Synthetic mobile application tests over all hours in the current date for all organizations.
synthetics_parallel_testing_max_slots_hwm (int, optional) – Shows the high-water mark of used synthetics parallel testing slots over all hours in the current date for all organizations.
trace_search_indexed_events_count_sum (int, optional) – Shows the sum of all Indexed Spans indexed over all hours in the current date for all organizations.
twol_ingested_events_bytes_sum (int, optional) – Shows the sum of all ingested APM span bytes over all hours in the current date for all organizations.
universal_service_monitoring_host_top99p (int, optional) – Shows the 99th percentile of all universal service management hosts over all hours in the current date for the given org.
vsphere_host_top99p (int, optional) – Shows the 99th percentile of all vSphere hosts over all hours in the current date for all organizations.
vuln_management_host_count_top99p (int, optional) – Shows the 99th percentile of all Application Vulnerability Management hosts over all hours in the current date for the given org.
workflow_executions_usage_sum (int, optional) – Sum of all workflows executed over all hours in the current date for all organizations.

usage_summary_date_org¶

class UsageSummaryDateOrg(*args, **kwargs)¶

Bases: ModelNormal

Global hourly report of all data billed by Datadog for a given organization.

Parameters:

agent_host_top99p (int, optional) – Shows the 99th percentile of all agent hosts over all hours in the current date for the given org.
apm_azure_app_service_host_top99p (int, optional) – Shows the 99th percentile of all Azure app services using APM over all hours in the current date for the given org.
apm_devsecops_host_top99p (int, optional) – Shows the 99th percentile of all APM DevSecOps hosts over all hours in the current date for the given org.
apm_fargate_count_avg (int, optional) – Shows the average of all APM ECS Fargate tasks over all hours in the current months for the given org.
apm_host_top99p (int, optional) – Shows the 99th percentile of all distinct APM hosts over all hours in the current date for the given org.
appsec_fargate_count_avg (int, optional) – Shows the average of all Application Security Monitoring ECS Fargate tasks over all hours in the current months for the given org.
audit_logs_lines_indexed_sum (int, optional) – Shows the sum of all audit logs lines indexed over all hours in the current date for the given org. Deprecated.
audit_trail_enabled_hwm (int, optional) – Shows whether Audit Trail is enabled for the current date for the given org.
avg_profiled_fargate_tasks (int, optional) – The average profiled task count for Fargate Profiling.
aws_host_top99p (int, optional) – Shows the 99th percentile of all AWS hosts over all hours in the current date for the given org.
aws_lambda_func_count (int, optional) – Shows the sum of all AWS Lambda invocations over all hours in the current date for the given org.
aws_lambda_invocations_sum (int, optional) – Shows the sum of all AWS Lambda invocations over all hours in the current date for the given org.
azure_app_service_top99p (int, optional) – Shows the 99th percentile of all Azure app services over all hours in the current date for the given org.
billable_ingested_bytes_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current date for the given org.
browser_rum_lite_session_count_sum (int, optional) – Shows the sum of all browser lite sessions over all hours in the current date for the given org.
browser_rum_replay_session_count_sum (int, optional) – Shows the sum of all browser replay sessions over all hours in the current date for the given org.
browser_rum_units_sum (int, optional) – Shows the sum of all browser RUM units over all hours in the current date for the given org.
ci_pipeline_indexed_spans_sum (int, optional) – Shows the sum of all CI pipeline indexed spans over all hours in the current date for the given org.
ci_test_indexed_spans_sum (int, optional) – Shows the sum of all CI test indexed spans over all hours in the current date for the given org.
ci_visibility_itr_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility intelligent test runner committers over all hours in the current date for the given org.
ci_visibility_pipeline_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility pipeline committers over all hours in the current date for the given org.
ci_visibility_test_committers_hwm (int, optional) – Shows the high-water mark of all CI visibility test committers over all hours in the current date for the given org.
cloud_cost_management_aws_host_count_avg (int, optional) – Host count average of Cloud Cost Management for AWS for the given date and given org.
cloud_cost_management_azure_host_count_avg (int, optional) – Host count average of Cloud Cost Management for Azure for the given date and given org.
cloud_cost_management_host_count_avg (int, optional) – Host count average of Cloud Cost Management for all cloud providers for the given date and given org.
cloud_siem_events_sum (int, optional) – Shows the sum of all Cloud Security Information and Event Management events over all hours in the current date for the given org.
container_avg (int, optional) – Shows the average of all distinct containers over all hours in the current date for the given org.
container_excl_agent_avg (int, optional) – Shows the average of containers without the Datadog Agent over all hours in the current date for the given organization.
container_hwm (int, optional) – Shows the high-water mark of all distinct containers over all hours in the current date for the given org.
csm_container_enterprise_compliance_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise compliance containers over all hours in the current date for the given org.
csm_container_enterprise_cws_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise Cloud Workload Security containers over all hours in the current date for the given org.
csm_container_enterprise_total_count_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise containers over all hours in the current date for the given org.
csm_host_enterprise_aas_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure app services hosts over all hours in the current date for the given org.
csm_host_enterprise_aws_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise AWS hosts over all hours in the current date for the given org.
csm_host_enterprise_azure_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure hosts over all hours in the current date for the given org.
csm_host_enterprise_compliance_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise compliance hosts over all hours in the current date for the given org.
csm_host_enterprise_cws_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Cloud Workload Security hosts over all hours in the current date for the given org.
csm_host_enterprise_gcp_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise GCP hosts over all hours in the current date for the given org.
csm_host_enterprise_total_host_count_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise hosts over all hours in the current date for the given org.
cspm_aas_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure app services hosts over all hours in the current date for the given org.
cspm_aws_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro AWS hosts over all hours in the current date for the given org.
cspm_azure_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure hosts over all hours in the current date for the given org.
cspm_container_avg (int, optional) – Shows the average number of Cloud Security Management Pro containers over all hours in the current date for the given org.
cspm_container_hwm (int, optional) – Shows the high-water mark of Cloud Security Management Pro containers over all hours in the current date for the given org.
cspm_gcp_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro GCP hosts over all hours in the current date for the given org.
cspm_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro hosts over all hours in the current date for the given org.
custom_historical_ts_avg (int, optional) – Shows the average number of distinct historical custom metrics over all hours in the current date for the given org.
custom_live_ts_avg (int, optional) – Shows the average number of distinct live custom metrics over all hours in the current date for the given org.
custom_ts_avg (int, optional) – Shows the average number of distinct custom metrics over all hours in the current date for the given org.
cws_container_count_avg (int, optional) – Shows the average of all distinct Cloud Workload Security containers over all hours in the current date for the given org.
cws_host_top99p (int, optional) – Shows the 99th percentile of all Cloud Workload Security hosts over all hours in the current date for the given org.
dbm_host_top99p_sum (int, optional) – Shows the 99th percentile of all Database Monitoring hosts over all hours in the current month for the given org.
dbm_queries_avg_sum (int, optional) – Shows the average of all distinct Database Monitoring normalized queries over all hours in the current month for the given org.
fargate_tasks_count_avg (int, optional) – The average task count for Fargate.
fargate_tasks_count_hwm (int, optional) – Shows the high-water mark of all Fargate tasks over all hours in the current date for the given org.
forwarding_events_bytes_sum (int, optional) – Shows the sum of all log bytes forwarded over all hours in the current date for the given org.
gcp_host_top99p (int, optional) – Shows the 99th percentile of all GCP hosts over all hours in the current date for the given org.
heroku_host_top99p (int, optional) – Shows the 99th percentile of all Heroku dynos over all hours in the current date for the given org.
id (str, optional) – The organization id.
incident_management_monthly_active_users_hwm (int, optional) – Shows the high-water mark of incident management monthly active users over all hours in the current date for the given org.
indexed_events_count_sum (int, optional) – Shows the sum of all log events indexed over all hours in the current date for the given org.
infra_host_top99p (int, optional) – Shows the 99th percentile of all distinct infrastructure hosts over all hours in the current date for the given org.
ingested_events_bytes_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current date for the given org.
iot_device_agg_sum (int, optional) – Shows the sum of all IoT devices over all hours in the current date for the given org.
iot_device_top99p_sum (int, optional) – Shows the 99th percentile of all IoT devices over all hours in the current date for the given org.
mobile_rum_lite_session_count_sum (int, optional) – Shows the sum of all mobile lite sessions over all hours in the current date for the given org.
mobile_rum_session_count_android_sum (int, optional) – Shows the sum of all mobile RUM Sessions on Android over all hours in the current date for the given org.
mobile_rum_session_count_flutter_sum (int, optional) – Shows the sum of all mobile RUM Sessions on Flutter over all hours in the current date for the given org.
mobile_rum_session_count_ios_sum (int, optional) – Shows the sum of all mobile RUM Sessions on iOS over all hours in the current date for the given org.
mobile_rum_session_count_reactnative_sum (int, optional) – Shows the sum of all mobile RUM Sessions on React Native over all hours in the current date for the given org.
mobile_rum_session_count_roku_sum (int, optional) – Shows the sum of all mobile RUM Sessions on Roku over all hours in the current date for the given org.
mobile_rum_session_count_sum (int, optional) – Shows the sum of all mobile RUM Sessions over all hours in the current date for the given org.
mobile_rum_units_sum (int, optional) – Shows the sum of all mobile RUM units over all hours in the current date for the given org.
name (str, optional) – The organization name.
ndm_netflow_events_sum (int, optional) – Shows the sum of all Network Device Monitoring NetFlow events over all hours in the current date for the given org.
netflow_indexed_events_count_sum (int, optional) – Shows the sum of all Network flows indexed over all hours in the current date for the given org.
npm_host_top99p (int, optional) – Shows the 99th percentile of all distinct Networks hosts over all hours in the current date for the given org.
observability_pipelines_bytes_processed_sum (int, optional) – Sum of all observability pipelines bytes processed over all hours in the current date for the given org.
online_archive_events_count_sum (int, optional) – Sum of all online archived events over all hours in the current date for the given org.
opentelemetry_apm_host_top99p (int, optional) – Shows the 99th percentile of APM hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for the given org.
opentelemetry_host_top99p (int, optional) – Shows the 99th percentile of all hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current date for the given org.
profiling_aas_count_top99p (int, optional) – Shows the 99th percentile of all profiled Azure app services over all hours in the current date for all organizations.
profiling_host_top99p (int, optional) – Shows the 99th percentile of all profiled hosts over all hours in the current date for the given org.
public_id (str, optional) – The organization public id.
region (str, optional) – The region of the organization.
rum_browser_and_mobile_session_count (int, optional) – Shows the sum of all mobile sessions and all browser lite and legacy sessions over all hours in the current date for the given org.
rum_session_count_sum (int, optional) – Shows the sum of all browser RUM Lite Sessions over all hours in the current date for the given org.
rum_total_session_count_sum (int, optional) – Shows the sum of RUM Sessions (browser and mobile) over all hours in the current date for the given org.
rum_units_sum (int, optional) – Shows the sum of all browser and mobile RUM units over all hours in the current date for the given org.
sds_apm_scanned_bytes_sum (int, optional) – Sum of all APM bytes scanned with sensitive data scanner over all hours in the current date for the given org.
sds_events_scanned_bytes_sum (int, optional) – Sum of all event stream events bytes scanned with sensitive data scanner over all hours in the current date for the given org.
sds_logs_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned of logs usage by the Sensitive Data Scanner over all hours in the current month for the given org.
sds_rum_scanned_bytes_sum (int, optional) – Sum of all RUM bytes scanned with sensitive data scanner over all hours in the current date for the given org.
sds_total_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned across all usage types by the Sensitive Data Scanner over all hours in the current month for the given org.
serverless_apps_azure_count_avg (int, optional) – Shows the average of the number of Serverless Apps for Azure for the given date and given org.
serverless_apps_google_count_avg (int, optional) – Shows the average of the number of Serverless Apps for Google Cloud for the given date and given org.
serverless_apps_total_count_avg (int, optional) – Shows the average of the number of Serverless Apps for Azure and Google Cloud for the given date and given org.
synthetics_browser_check_calls_count_sum (int, optional) – Shows the sum of all Synthetic browser tests over all hours in the current date for the given org.
synthetics_check_calls_count_sum (int, optional) – Shows the sum of all Synthetic API tests over all hours in the current date for the given org.
synthetics_mobile_test_runs_sum (int, optional) – Shows the sum of all Synthetic mobile application tests over all hours in the current date for the given org.
synthetics_parallel_testing_max_slots_hwm (int, optional) – Shows the high-water mark of used synthetics parallel testing slots over all hours in the current date for the given org.
trace_search_indexed_events_count_sum (int, optional) – Shows the sum of all Indexed Spans indexed over all hours in the current date for the given org.
twol_ingested_events_bytes_sum (int, optional) – Shows the sum of all ingested APM span bytes over all hours in the current date for the given org.
universal_service_monitoring_host_top99p (int, optional) – Shows the 99th percentile of all Universal Service Monitoring hosts over all hours in the current date for the given org.
vsphere_host_top99p (int, optional) – Shows the 99th percentile of all vSphere hosts over all hours in the current date for the given org.
vuln_management_host_count_top99p (int, optional) – Shows the 99th percentile of all Application Vulnerability Management hosts over all hours in the current date for the given org.
workflow_executions_usage_sum (int, optional) – Sum of all workflows executed over all hours in the current date for the given org.

usage_summary_response¶

class UsageSummaryResponse(*args, **kwargs)¶

Bases: ModelNormal

Response summarizing all usage aggregated across the months in the request for all organizations, and broken down by month and by organization.

Parameters:

agent_host_top99p_sum (int, optional) – Shows the 99th percentile of all agent hosts over all hours in the current months for all organizations.
apm_azure_app_service_host_top99p_sum (int, optional) – Shows the 99th percentile of all Azure app services using APM over all hours in the current months all organizations.
apm_devsecops_host_top99p_sum (int, optional) – Shows the 99th percentile of all APM DevSecOps hosts over all hours in the current months for all organizations.
apm_fargate_count_avg_sum (int, optional) – Shows the average of all APM ECS Fargate tasks over all hours in the current months for all organizations.
apm_host_top99p_sum (int, optional) – Shows the 99th percentile of all distinct APM hosts over all hours in the current months for all organizations.
appsec_fargate_count_avg_sum (int, optional) – Shows the average of all Application Security Monitoring ECS Fargate tasks over all hours in the current months for all organizations.
audit_logs_lines_indexed_agg_sum (int, optional) – Shows the sum of all audit logs lines indexed over all hours in the current months for all organizations. Deprecated.
audit_trail_enabled_hwm_sum (int, optional) – Shows the total number of organizations that had Audit Trail enabled over a specific number of months.
avg_profiled_fargate_tasks_sum (int, optional) – Shows the average of all profiled Fargate tasks over all hours in the current months for all organizations.
aws_host_top99p_sum (int, optional) – Shows the 99th percentile of all AWS hosts over all hours in the current months for all organizations.
aws_lambda_func_count (int, optional) – Shows the average of the number of functions that executed 1 or more times each hour in the current months for all organizations.
aws_lambda_invocations_sum (int, optional) – Shows the sum of all AWS Lambda invocations over all hours in the current months for all organizations.
azure_app_service_top99p_sum (int, optional) – Shows the 99th percentile of all Azure app services over all hours in the current months for all organizations.
azure_host_top99p_sum (int, optional) – Shows the 99th percentile of all Azure hosts over all hours in the current months for all organizations.
billable_ingested_bytes_agg_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current months for all organizations.
browser_rum_lite_session_count_agg_sum (int, optional) – Shows the sum of all browser lite sessions over all hours in the current months for all organizations.
browser_rum_replay_session_count_agg_sum (int, optional) – Shows the sum of all browser replay sessions over all hours in the current months for all organizations.
browser_rum_units_agg_sum (int, optional) – Shows the sum of all browser RUM units over all hours in the current months for all organizations.
ci_pipeline_indexed_spans_agg_sum (int, optional) – Shows the sum of all CI pipeline indexed spans over all hours in the current months for all organizations.
ci_test_indexed_spans_agg_sum (int, optional) – Shows the sum of all CI test indexed spans over all hours in the current months for all organizations.
ci_visibility_itr_committers_hwm_sum (int, optional) – Shows the high-water mark of all CI visibility intelligent test runner committers over all hours in the current months for all organizations.
ci_visibility_pipeline_committers_hwm_sum (int, optional) – Shows the high-water mark of all CI visibility pipeline committers over all hours in the current months for all organizations.
ci_visibility_test_committers_hwm_sum (int, optional) – Shows the high-water mark of all CI visibility test committers over all hours in the current months for all organizations.
cloud_cost_management_aws_host_count_avg_sum (int, optional) – Sum of the host count average for Cloud Cost Management for AWS.
cloud_cost_management_azure_host_count_avg_sum (int, optional) – Sum of the host count average for Cloud Cost Management for Azure.
cloud_cost_management_host_count_avg_sum (int, optional) – Sum of the host count average for Cloud Cost Management for all cloud providers.
cloud_siem_events_agg_sum (int, optional) – Shows the sum of all Cloud Security Information and Event Management events over all hours in the current months for all organizations.
container_avg_sum (int, optional) – Shows the average of all distinct containers over all hours in the current months for all organizations.
container_excl_agent_avg_sum (int, optional) – Shows the average of the containers without the Datadog Agent over all hours in the current month for all organizations.
container_hwm_sum (int, optional) – Shows the sum of the high-water marks of all distinct containers over all hours in the current months for all organizations.
csm_container_enterprise_compliance_count_agg_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise compliance containers over all hours in the current months for all organizations.
csm_container_enterprise_cws_count_agg_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise Cloud Workload Security containers over all hours in the current months for all organizations.
csm_container_enterprise_total_count_agg_sum (int, optional) – Shows the sum of all Cloud Security Management Enterprise containers over all hours in the current months for all organizations.
csm_host_enterprise_aas_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure app services hosts over all hours in the current months for all organizations.
csm_host_enterprise_aws_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise AWS hosts over all hours in the current months for all organizations.
csm_host_enterprise_azure_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Azure hosts over all hours in the current months for all organizations.
csm_host_enterprise_compliance_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise compliance hosts over all hours in the current months for all organizations.
csm_host_enterprise_cws_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise Cloud Workload Security hosts over all hours in the current months for all organizations.
csm_host_enterprise_gcp_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise GCP hosts over all hours in the current months for all organizations.
csm_host_enterprise_total_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Enterprise hosts over all hours in the current months for all organizations.
cspm_aas_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure app services hosts over all hours in the current months for all organizations.
cspm_aws_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro AWS hosts over all hours in the current months for all organizations.
cspm_azure_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro Azure hosts over all hours in the current months for all organizations.
cspm_container_avg_sum (int, optional) – Shows the average number of Cloud Security Management Pro containers over all hours in the current months for all organizations.
cspm_container_hwm_sum (int, optional) – Shows the sum of the the high-water marks of Cloud Security Management Pro containers over all hours in the current months for all organizations.
cspm_gcp_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro GCP hosts over all hours in the current months for all organizations.
cspm_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Security Management Pro hosts over all hours in the current months for all organizations.
custom_historical_ts_sum (int, optional) – Shows the average number of distinct historical custom metrics over all hours in the current months for all organizations.
custom_live_ts_sum (int, optional) – Shows the average number of distinct live custom metrics over all hours in the current months for all organizations.
custom_ts_sum (int, optional) – Shows the average number of distinct custom metrics over all hours in the current months for all organizations.
cws_containers_avg_sum (int, optional) – Shows the average of all distinct Cloud Workload Security containers over all hours in the current months for all organizations.
cws_host_top99p_sum (int, optional) – Shows the 99th percentile of all Cloud Workload Security hosts over all hours in the current months for all organizations.
dbm_host_top99p_sum (int, optional) – Shows the 99th percentile of all Database Monitoring hosts over all hours in the current month for all organizations.
dbm_queries_avg_sum (int, optional) – Shows the average of all distinct Database Monitoring Normalized Queries over all hours in the current month for all organizations.
end_date (datetime, optional) – Shows the last date of usage in the current months for all organizations.
fargate_tasks_count_avg_sum (int, optional) – Shows the average of all Fargate tasks over all hours in the current months for all organizations.
fargate_tasks_count_hwm_sum (int, optional) – Shows the sum of the high-water marks of all Fargate tasks over all hours in the current months for all organizations.
forwarding_events_bytes_agg_sum (int, optional) – Shows the sum of all logs forwarding bytes over all hours in the current months for all organizations (data available as of April 1, 2023)
gcp_host_top99p_sum (int, optional) – Shows the 99th percentile of all GCP hosts over all hours in the current months for all organizations.
heroku_host_top99p_sum (int, optional) – Shows the 99th percentile of all Heroku dynos over all hours in the current months for all organizations.
incident_management_monthly_active_users_hwm_sum (int, optional) – Shows sum of the the high-water marks of incident management monthly active users in the current months for all organizations.
indexed_events_count_agg_sum (int, optional) – Shows the sum of all log events indexed over all hours in the current months for all organizations.
infra_host_top99p_sum (int, optional) – Shows the 99th percentile of all distinct infrastructure hosts over all hours in the current months for all organizations.
ingested_events_bytes_agg_sum (int, optional) – Shows the sum of all log bytes ingested over all hours in the current months for all organizations.
iot_device_agg_sum (int, optional) – Shows the sum of all IoT devices over all hours in the current months for all organizations.
iot_device_top99p_sum (int, optional) – Shows the 99th percentile of all IoT devices over all hours in the current months of all organizations.
last_updated (datetime, optional) – Shows the the most recent hour in the current months for all organizations for which all usages were calculated.
live_indexed_events_agg_sum (int, optional) – Shows the sum of all live logs indexed over all hours in the current months for all organizations (data available as of December 1, 2020).
live_ingested_bytes_agg_sum (int, optional) – Shows the sum of all live logs bytes ingested over all hours in the current months for all organizations (data available as of December 1, 2020).
logs_by_retention (LogsByRetention, optional) – Object containing logs usage data broken down by retention period.
mobile_rum_lite_session_count_agg_sum (int, optional) – Shows the sum of all mobile lite sessions over all hours in the current months for all organizations.
mobile_rum_session_count_agg_sum (int, optional) – Shows the sum of all mobile RUM Sessions over all hours in the current months for all organizations.
mobile_rum_session_count_android_agg_sum (int, optional) – Shows the sum of all mobile RUM Sessions on Android over all hours in the current months for all organizations.
mobile_rum_session_count_flutter_agg_sum (int, optional) – Shows the sum of all mobile RUM Sessions on Flutter over all hours in the current months for all organizations.
mobile_rum_session_count_ios_agg_sum (int, optional) – Shows the sum of all mobile RUM Sessions on iOS over all hours in the current months for all organizations.
mobile_rum_session_count_reactnative_agg_sum (int, optional) – Shows the sum of all mobile RUM Sessions on React Native over all hours in the current months for all organizations.
mobile_rum_session_count_roku_agg_sum (int, optional) – Shows the sum of all mobile RUM Sessions on Roku over all hours in the current months for all organizations.
mobile_rum_units_agg_sum (int, optional) – Shows the sum of all mobile RUM units over all hours in the current months for all organizations.
ndm_netflow_events_agg_sum (int, optional) – Shows the sum of all Network Device Monitoring NetFlow events over all hours in the current months for all organizations.
netflow_indexed_events_count_agg_sum (int, optional) – Shows the sum of all Network flows indexed over all hours in the current months for all organizations.
npm_host_top99p_sum (int, optional) – Shows the 99th percentile of all distinct Networks hosts over all hours in the current months for all organizations.
observability_pipelines_bytes_processed_agg_sum (int, optional) – Sum of all observability pipelines bytes processed over all hours in the current months for all organizations.
online_archive_events_count_agg_sum (int, optional) – Sum of all online archived events over all hours in the current months for all organizations.
opentelemetry_apm_host_top99p_sum (int, optional) – Shows the 99th percentile of APM hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current months for all organizations.
opentelemetry_host_top99p_sum (int, optional) – Shows the 99th percentile of all hosts reported by the Datadog exporter for the OpenTelemetry Collector over all hours in the current months for all organizations.
profiling_aas_count_top99p_sum (int, optional) – Shows the 99th percentile of all profiled Azure app services over all hours in the current months for all organizations.
profiling_container_agent_count_avg (int, optional) – Shows the average number of profiled containers over all hours in the current months for all organizations.
profiling_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all profiled hosts over all hours in the current months for all organizations.
rehydrated_indexed_events_agg_sum (int, optional) – Shows the sum of all rehydrated logs indexed over all hours in the current months for all organizations (data available as of December 1, 2020).
rehydrated_ingested_bytes_agg_sum (int, optional) – Shows the sum of all rehydrated logs bytes ingested over all hours in the current months for all organizations (data available as of December 1, 2020).
rum_browser_and_mobile_session_count (int, optional) – Shows the sum of all mobile sessions and all browser lite and legacy sessions over all hours in the current month for all organizations.
rum_session_count_agg_sum (int, optional) – Shows the sum of all browser RUM Lite Sessions over all hours in the current months for all organizations.
rum_total_session_count_agg_sum (int, optional) – Shows the sum of RUM Sessions (browser and mobile) over all hours in the current months for all organizations.
rum_units_agg_sum (int, optional) – Shows the sum of all browser and mobile RUM units over all hours in the current months for all organizations.
sds_apm_scanned_bytes_sum (int, optional) – Sum of all APM bytes scanned with sensitive data scanner in the current months for all organizations.
sds_events_scanned_bytes_sum (int, optional) – Sum of all event stream events bytes scanned with sensitive data scanner in the current months for all organizations.
sds_logs_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned of logs usage by the Sensitive Data Scanner over all hours in the current month for all organizations.
sds_rum_scanned_bytes_sum (int, optional) – Sum of all RUM bytes scanned with sensitive data scanner in the current months for all organizations.
sds_total_scanned_bytes_sum (int, optional) – Shows the sum of all bytes scanned across all usage types by the Sensitive Data Scanner over all hours in the current month for all organizations.
serverless_apps_azure_count_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Azure in the current months for all organizations.
serverless_apps_google_count_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Google Cloud in the current months for all organizations.
serverless_apps_total_count_avg_sum (int, optional) – Sum of the average number of Serverless Apps for Azure and Google Cloud in the current months for all organizations.
start_date (datetime, optional) – Shows the first date of usage in the current months for all organizations.
synthetics_browser_check_calls_count_agg_sum (int, optional) – Shows the sum of all Synthetic browser tests over all hours in the current months for all organizations.
synthetics_check_calls_count_agg_sum (int, optional) – Shows the sum of all Synthetic API tests over all hours in the current months for all organizations.
synthetics_mobile_test_runs_agg_sum (int, optional) – Shows the sum of Synthetic mobile application tests over all hours in the current months for all organizations.
synthetics_parallel_testing_max_slots_hwm_sum (int, optional) – Shows the sum of the high-water marks of used synthetics parallel testing slots over all hours in the current month for all organizations.
trace_search_indexed_events_count_agg_sum (int, optional) – Shows the sum of all Indexed Spans indexed over all hours in the current months for all organizations.
twol_ingested_events_bytes_agg_sum (int, optional) – Shows the sum of all ingested APM span bytes over all hours in the current months for all organizations.
universal_service_monitoring_host_top99p_sum (int, optional) – Shows the 99th percentile of all Universal Service Monitoring hosts over all hours in the current months for all organizations.
usage ([UsageSummaryDate], optional) – An array of objects regarding hourly usage.
vsphere_host_top99p_sum (int, optional) – Shows the 99th percentile of all vSphere hosts over all hours in the current months for all organizations.
vuln_management_host_count_top99p_sum (int, optional) – Shows the 99th percentile of all Application Vulnerability Management hosts over all hours in the current months for all organizations.
workflow_executions_usage_agg_sum (int, optional) – Sum of all workflows executed over all hours in the current months for all organizations.

usage_synthetics_api_hour¶

class UsageSyntheticsAPIHour(*args, **kwargs)¶

Bases: ModelNormal

Number of Synthetics API tests run for each hour for a given organization.

Parameters:

check_calls_count (int, none_type, optional) – Contains the number of Synthetics API tests run.
hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_synthetics_api_response¶

class UsageSyntheticsAPIResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of Synthetics API tests run for each hour for a given organization.

Parameters:: usage ([UsageSyntheticsAPIHour], optional) – Get hourly usage for Synthetics API tests.

usage_synthetics_browser_hour¶

class UsageSyntheticsBrowserHour(*args, **kwargs)¶

Bases: ModelNormal

Number of Synthetics Browser tests run for each hour for a given organization.

Parameters:

browser_check_calls_count (int, none_type, optional) – Contains the number of Synthetics Browser tests run.
hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_synthetics_browser_response¶

class UsageSyntheticsBrowserResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of Synthetics Browser tests run for each hour for a given organization.

Parameters:: usage ([UsageSyntheticsBrowserHour], optional) – Get hourly usage for Synthetics Browser tests.

usage_synthetics_hour¶

class UsageSyntheticsHour(*args, **kwargs)¶

Bases: ModelNormal

The number of synthetics tests run for each hour for a given organization.

Parameters:

check_calls_count (int, optional) – Contains the number of Synthetics API tests run.
hour (datetime, optional) – The hour for the usage.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_synthetics_response¶

class UsageSyntheticsResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of Synthetics API tests run for each hour for a given organization.

Parameters:: usage ([UsageSyntheticsHour], optional) – Array with the number of hourly Synthetics test run for a given organization.

usage_timeseries_hour¶

class UsageTimeseriesHour(*args, **kwargs)¶

Bases: ModelNormal

The hourly usage of timeseries.

Parameters:

hour (datetime, optional) – The hour for the usage.
num_custom_input_timeseries (int, optional) – Contains the number of custom metrics that are inputs for aggregations (metric configured is custom).
num_custom_output_timeseries (int, optional) – Contains the number of custom metrics that are outputs for aggregations (metric configured is custom).
num_custom_timeseries (int, optional) – Contains sum of non-aggregation custom metrics and custom metrics that are outputs for aggregations.
org_name (str, optional) – The organization name.
public_id (str, optional) – The organization public ID.

usage_timeseries_response¶

class UsageTimeseriesResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing hourly usage of timeseries.

Parameters:: usage ([UsageTimeseriesHour], optional) – An array of objects regarding hourly usage of timeseries.

usage_top_avg_metrics_hour¶

class UsageTopAvgMetricsHour(*args, **kwargs)¶

Bases: ModelNormal

Number of hourly recorded custom metrics for a given organization.

Parameters:

avg_metric_hour (int, optional) – Average number of timeseries per hour in which the metric occurs.
max_metric_hour (int, optional) – Maximum number of timeseries per hour in which the metric occurs.
metric_category (UsageMetricCategory, optional) – Contains the metric category.
metric_name (str, optional) – Contains the custom metric name.

usage_top_avg_metrics_metadata¶

class UsageTopAvgMetricsMetadata(*args, **kwargs)¶

Bases: ModelNormal

The object containing document metadata.

Parameters:

day (datetime, optional) – The day value from the user request that contains the returned usage data. (If day was used the request)
month (datetime, optional) – The month value from the user request that contains the returned usage data. (If month was used the request)
pagination (UsageTopAvgMetricsPagination, optional) – The metadata for the current pagination.

usage_top_avg_metrics_pagination¶

class UsageTopAvgMetricsPagination(*args, **kwargs)¶

Bases: ModelNormal

The metadata for the current pagination.

Parameters:

limit (int, optional) – Maximum amount of records to be returned.
next_record_id (str, none_type, optional) – The cursor to get the next results (if any). To make the next request, use the same parameters and add next_record_id.
total_number_of_records (int, none_type, optional) – Total number of records.

usage_top_avg_metrics_response¶

class UsageTopAvgMetricsResponse(*args, **kwargs)¶

Bases: ModelNormal

Response containing the number of hourly recorded custom metrics for a given organization.

Parameters:

metadata (UsageTopAvgMetricsMetadata, optional) – The object containing document metadata.
usage ([UsageTopAvgMetricsHour], optional) – Number of hourly recorded custom metrics for a given organization.

user¶

class User(*args, **kwargs)¶

Bases: ModelNormal

Create, edit, and disable users.

Parameters:

access_role (AccessRole, none_type, optional) – The access role of the user. Options are st (standard user), adm (admin user), or ro (read-only user).
disabled (bool, optional) – The new disabled status of the user.
email (str, optional) – The new email of the user.
handle (str, optional) – The user handle, must be a valid email.
icon (str, optional) – Gravatar icon associated to the user.
name (str, optional) – The name of the user.
verified (bool, optional) – Whether or not the user logged in Datadog at least once.

user_disable_response¶

class UserDisableResponse(*args, **kwargs)¶

Bases: ModelNormal

Array of user disabled for a given organization.

Parameters:: message (str, optional) – Information pertaining to a user disabled for a given organization.

user_list_response¶

class UserListResponse(*args, **kwargs)¶

Bases: ModelNormal

Array of Datadog users for a given organization.

Parameters:: users ([User], optional) – Array of users.

user_response¶

class UserResponse(*args, **kwargs)¶

Bases: ModelNormal

A Datadog User.

Parameters:: user (User, optional) – Create, edit, and disable users.

webhooks_integration¶

class WebhooksIntegration(*args, **kwargs)¶

Bases: ModelNormal

Datadog-Webhooks integration.

Parameters:

custom_headers (str, none_type, optional) – If null , uses no header. If given a JSON payload, these will be headers attached to your webhook.
encode_as (WebhooksIntegrationEncoding, optional) – Encoding type. Can be given either json or form.
name (str) – The name of the webhook. It corresponds with <WEBHOOK_NAME>. Learn more on how to use it in monitor notifications.
payload (str, none_type, optional) – If null , uses the default payload. If given a JSON payload, the webhook returns the payload specified by the given payload. Webhooks variable usage.
url (str) – URL of the webhook.

webhooks_integration_custom_variable¶

class WebhooksIntegrationCustomVariable(*args, **kwargs)¶

Bases: ModelNormal

Custom variable for Webhook integration.

Parameters:

is_secret (bool) – Make custom variable is secret or not. If the custom variable is secret, the value is not returned in the response payload.
name (str) – The name of the variable. It corresponds with <CUSTOM_VARIABLE_NAME>.
value (str) – Value of the custom variable.

webhooks_integration_custom_variable_response¶

class WebhooksIntegrationCustomVariableResponse(*args, **kwargs)¶

Bases: ModelNormal

Custom variable for Webhook integration.

Parameters:

is_secret (bool) – Make custom variable is secret or not. If the custom variable is secret, the value is not returned in the response payload.
name (str) – The name of the variable. It corresponds with <CUSTOM_VARIABLE_NAME>. It must only contains upper-case characters, integers or underscores.
value (str, optional) – Value of the custom variable. It won’t be returned if the variable is secret.

webhooks_integration_custom_variable_update_request¶

class WebhooksIntegrationCustomVariableUpdateRequest(*args, **kwargs)¶

Bases: ModelNormal

Update request of a custom variable object.

All properties are optional.

Parameters:

is_secret (bool, optional) – Make custom variable is secret or not. If the custom variable is secret, the value is not returned in the response payload.
name (str, optional) – The name of the variable. It corresponds with <CUSTOM_VARIABLE_NAME>. It must only contains upper-case characters, integers or underscores.
value (str, optional) – Value of the custom variable.

webhooks_integration_encoding¶

class WebhooksIntegrationEncoding(*args, **kwargs)¶

Bases: ModelSimple

Encoding type. Can be given either json or form.

Parameters:

value (str) – If omitted defaults to “json”. Must be one of [“json”, “form”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

webhooks_integration_update_request¶

class WebhooksIntegrationUpdateRequest(*args, **kwargs)¶

Bases: ModelNormal

Update request of a Webhooks integration object.

All properties are optional.

Parameters:

custom_headers (str, optional) – If null , uses no header. If given a JSON payload, these will be headers attached to your webhook.
encode_as (WebhooksIntegrationEncoding, optional) – Encoding type. Can be given either json or form.
name (str, optional) –
The name of the webhook. It corresponds with <WEBHOOK_NAME>. Learn more on how to use it in monitor notifications.
payload (str, none_type, optional) –
If null , uses the default payload. If given a JSON payload, the webhook returns the payload specified by the given payload. Webhooks variable usage.
url (str, optional) – URL of the webhook.

class Widget(*args, **kwargs)¶

Bases: ModelNormal

Information about widget.

NoteThe layout property is required for widgets in dashboards with free layout_type.: For the new dashboard layout , the layout property depends on the reflow_type of the dashboard.

- If `reflow_type` is `fixed`, `layout` is required.
- If `reflow_type` is `auto`, `layout` should not be set.

Parameters:

definition (WidgetDefinition) – Definition of the widget.
id (int, optional) – ID of the widget.
layout (WidgetLayout, optional) – The layout for a widget on a free or new dashboard layout dashboard.

widget_aggregator¶

class WidgetAggregator(*args, **kwargs)¶

Bases: ModelSimple

Aggregator used for the request.

Parameters:

value (str) – Must be one of [“avg”, “last”, “max”, “min”, “sum”, “percentile”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_axis¶

class WidgetAxis(*args, **kwargs)¶

Bases: ModelNormal

Axis controls for the widget.

Parameters:

include_zero (bool, optional) – Set to true to include zero.
label (str, optional) – The label of the axis to display on the graph. Only usable on Scatterplot Widgets.
max (str, optional) – Specifies maximum numeric value to show on the axis. Defaults to auto.
min (str, optional) – Specifies minimum numeric value to show on the axis. Defaults to auto.
scale (str, optional) – Specifies the scale type. Possible values are linear , log , sqrt , and pow## (for example pow2 or pow0.5 ).

widget_change_type¶

class WidgetChangeType(*args, **kwargs)¶

Bases: ModelSimple

Show the absolute or the relative change.

Parameters:

value (str) – Must be one of [“absolute”, “relative”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_color_preference¶

class WidgetColorPreference(*args, **kwargs)¶

Bases: ModelSimple

Which color to use on the widget.

Parameters:

value (str) – Must be one of [“background”, “text”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_comparator¶

class WidgetComparator(*args, **kwargs)¶

Bases: ModelSimple

Comparator to apply.

Parameters:

value (str) – Must be one of [“=”, “>”, “>=”, “<”, “<=”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_compare_to¶

class WidgetCompareTo(*args, **kwargs)¶

Bases: ModelSimple

Timeframe used for the change comparison.

Parameters:

value (str) – Must be one of [“hour_before”, “day_before”, “week_before”, “month_before”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_conditional_format¶

class WidgetConditionalFormat(*args, **kwargs)¶

Bases: ModelNormal

Define a conditional format for the widget.

Parameters:

comparator (WidgetComparator) – Comparator to apply.
custom_bg_color (str, optional) – Color palette to apply to the background, same values available as palette.
custom_fg_color (str, optional) – Color palette to apply to the foreground, same values available as palette.
hide_value (bool, optional) – True hides values.
image_url (str, optional) – Displays an image as the background.
metric (str, optional) – Metric from the request to correlate this conditional format with.
palette (WidgetPalette) – Color palette to apply.
timeframe (str, optional) – Defines the displayed timeframe.
value (float) – Value for the comparator.

widget_custom_link¶

class WidgetCustomLink(*args, **kwargs)¶

Bases: ModelNormal

Custom links help you connect a data value to a URL, like a Datadog page or your AWS console.

Parameters:

is_hidden (bool, optional) – The flag for toggling context menu link visibility.
label (str, optional) – The label for the custom link URL. Keep the label short and descriptive. Use metrics and tags as variables.
link (str, optional) – The URL of the custom link. URL must include http or https. A relative URL must start with /.
override_label (str, optional) – The label ID that refers to a context menu link. Can be logs , hosts , traces , profiles , processes , containers , or rum.

widget_definition¶

class WidgetDefinition(*args, **kwargs)¶

Bases: ModelComposed

Definition of the widget.

Parameters:

alert_id (str) – ID of the alert to use in the widget.
time (WidgetTime, optional) – Time setting for the widget.
title (str, optional) – The title of the widget.
title_align (WidgetTextAlign, optional) – How to align the text on the widget.
title_size (str, optional) – Size of the title.
type (AlertGraphWidgetDefinitionType) – Type of the alert graph widget.
viz_type (WidgetVizType) – Whether to display the Alert Graph as a timeseries or a top list.
precision (int, optional) – Number of decimal to show. If not defined, will use the raw value.
text_align (WidgetTextAlign, optional) – How to align the text on the widget.
unit (str, optional) – Unit to display with the value.
custom_links ([WidgetCustomLink], optional) – List of custom links.
requests ([ChangeWidgetRequest]) –
Array of one request object to display in the widget.

See the dedicated [Request JSON schema documentation](https://docs.datadoghq.com/dashboards/graphing_json/request_json)
to learn how to build the REQUEST_SCHEMA.
check (str) – Name of the check to use in the widget.
group (str, optional) – Group reporting a single check.
group_by ([str], optional) – List of tag prefixes to group by in the case of a cluster check.
grouping (WidgetGrouping) – The kind of grouping to use.
tags ([str], optional) – List of tags used to filter the groups reporting a cluster check.
legend_size (str, optional) – (Deprecated) The widget legend was replaced by a tooltip and sidebar.
markers ([WidgetMarker], optional) – List of markers.
show_legend (bool, optional) – (Deprecated) The widget legend was replaced by a tooltip and sidebar.
xaxis (DistributionWidgetXAxis, optional) – X Axis controls for the distribution widget.
yaxis (DistributionWidgetYAxis, optional) – Y Axis controls for the distribution widget.
event_size (WidgetEventSize, optional) – Size to use to display an event.
query (str) – Query to filter the event stream with.
tags_execution (str, optional) – The execution method for multi-value filters. Can be either and or or.
color (str, optional) – Color of the text.
font_size (str, optional) – Size of the text.
text (str) – Text to display.
style (GeomapWidgetDefinitionStyle) – The style to apply to the widget.
view (GeomapWidgetDefinitionView) – The view of the world that the map should render.
background_color (str, optional) – Background color of the group title.
banner_img (str, optional) – URL of image to display as a banner for the group.
layout_type (WidgetLayoutType) – Layout type of the group.
show_title (bool, optional) – Whether to show the title or not.
widgets ([Widget]) – List of widget groups.
events ([WidgetEvent], optional) – List of widget events.
no_group_hosts (bool, optional) – Whether to show the hosts that don’t fit in a group.
no_metric_hosts (bool, optional) – Whether to show the hosts with no metrics.
node_type (WidgetNodeType, optional) – Which type of node to use in the map.
notes (str, optional) – Notes on the title.
scope ([str], optional) – List of tags used to filter the map.
url (str) – URL of the iframe.
has_background (bool, optional) – Whether to display a background or not.
has_border (bool, optional) – Whether to display a border or not.
horizontal_align (WidgetHorizontalAlign, optional) – Horizontal alignment.
margin (WidgetMargin, optional) – Size of the margins around the image. Note: small and large values are deprecated.
sizing (WidgetImageSizing, optional) – How to size the image on the widget. The values are based on the image object-fit CSS properties. Note: zoom, fit and center values are deprecated.
url_dark_theme (str, optional) – URL of the image in dark mode.
vertical_align (WidgetVerticalAlign, optional) – Vertical alignment.
columns ([str], optional) – Which columns to display on the widget.
indexes ([str], optional) – An array of index names to query in the stream. Use [] to query all indexes at once.
logset (str, optional) – ID of the log set to use.
message_display (WidgetMessageDisplay, optional) – Amount of log lines to display
show_date_column (bool, optional) – Whether to show the date column or not
show_message_column (bool, optional) – Whether to show the message column or not
sort (WidgetFieldSort, optional) – Which column and order to sort by
color_preference (WidgetColorPreference, optional) – Which color to use on the widget.
count (int, optional) – The number of monitors to display.
display_format (WidgetMonitorSummaryDisplayFormat, optional) – What to display on the widget.
hide_zero_counts (bool, optional) – Whether to show counts of 0 or not.
show_last_triggered (bool, optional) – Whether to show the time that has elapsed since the monitor/group triggered.
show_priority (bool, optional) – Whether to show the priorities column.
start (int, optional) – The start of the list. Typically 0.
summary_type (WidgetSummaryType, optional) – Which summary type should be used.
content (str) – Content of the note.
has_padding (bool, optional) – Whether to add padding or not.
show_tick (bool, optional) – Whether to show a tick or not.
tick_edge (WidgetTickEdge, optional) – Define how you want to align the text on the widget.
tick_pos (str, optional) – Where to position the tick on an edge.
powerpack_id (str) – UUID of the associated powerpack.
template_variables (PowerpackTemplateVariables, optional) – Powerpack template variables.
autoscale (bool, optional) – Whether to use auto-scaling or not.
custom_unit (str, optional) – Display a unit of your choice on the widget.
timeseries_background (TimeseriesBackground, optional) – Set a timeseries on the widget background.
inputs ([RunWorkflowWidgetInput], optional) – Array of workflow inputs to map to dashboard template variables.
workflow_id (str) – Workflow id.
additional_query_filters (str, optional) – Additional filters applied to the SLO query.
global_time_target (str, optional) – Defined global time target.
show_error_budget (bool, optional) – Defined error budget.
slo_id (str, optional) – ID of the SLO displayed.
time_windows ([WidgetTimeWindows], optional) – Times being monitored.
view_mode (WidgetViewMode, optional) – Define how you want the SLO to be displayed.
view_type (str) – Type of view displayed by the widget.
color_by_groups ([str], optional) – List of groups used for colors.
filters ([str]) – Your environment and primary tag (or * if enabled for your account).
service (str) – The ID of the service you want to map.
env (str) – APM environment.
show_breakdown (bool, optional) – Whether to show the latency breakdown or not.
show_distribution (bool, optional) – Whether to show the latency distribution or not.
show_errors (bool, optional) – Whether to show the error metrics or not.
show_hits (bool, optional) – Whether to show the hits metrics or not.
show_latency (bool, optional) – Whether to show the latency metrics or not.
show_resource_list (bool, optional) – Whether to show the resource list or not.
size_format (WidgetSizeFormat, optional) – Size of the widget.
span_name (str) – APM span name.
has_uniform_y_axes (bool, optional) – Normalize y axes across graphs
size (SplitGraphVizSize) – Size of the individual graphs in the split.
source_widget_definition (SplitGraphSourceWidgetDefinition) – The original widget we are splitting on.
split_config (SplitConfig) – Encapsulates all user choices about how to split a graph.
hide_total (bool, optional) – Show the total value in this widget.
legend (SunburstWidgetLegend, optional) – Configuration of the legend.
has_search_bar (TableWidgetHasSearchBar, optional) – Controls the display of the search bar.
legend_columns ([TimeseriesWidgetLegendColumn], optional) – Columns displayed in the legend.
legend_layout (TimeseriesWidgetLegendLayout, optional) – Layout of the legend.
right_yaxis (WidgetAxis, optional) – Axis controls for the widget.
color_by (TreeMapColorBy, optional) – (deprecated) The attribute formerly used to determine color in the widget.
size_by (TreeMapSizeBy, optional) – (deprecated) The attribute formerly used to determine size in the widget.

widget_display_type¶

class WidgetDisplayType(*args, **kwargs)¶

Bases: ModelSimple

Type of display to use for the request.

Parameters:

value (str) – Must be one of [“area”, “bars”, “line”, “overlay”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_event¶

class WidgetEvent(*args, **kwargs)¶

Bases: ModelNormal

Event overlay control options.

See the dedicated Events JSON schema documentation to learn how to build the <EVENTS_SCHEMA>.

Parameters:

q (str) – Query definition.
tags_execution (str, optional) – The execution method for multi-value filters.

widget_event_size¶

class WidgetEventSize(*args, **kwargs)¶

Bases: ModelSimple

Size to use to display an event.

Parameters:

value (str) – Must be one of [“s”, “l”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_field_sort¶

class WidgetFieldSort(*args, **kwargs)¶

Bases: ModelNormal

Which column and order to sort by

Parameters:

column (str) – Facet path for the column
order (WidgetSort) – Widget sorting methods.

widget_formula¶

class WidgetFormula(*args, **kwargs)¶

Bases: ModelNormal

Formula to be used in a widget query.

Parameters:

alias (str, optional) – Expression alias.
cell_display_mode (TableWidgetCellDisplayMode, optional) – Define a display mode for the table cell.
conditional_formats ([WidgetConditionalFormat], optional) – List of conditional formats.
formula (str) – String expression built from queries, formulas, and functions.
limit (WidgetFormulaLimit, optional) – Options for limiting results returned.
style (WidgetFormulaStyle, optional) – Styling options for widget formulas.

widget_formula_limit¶

class WidgetFormulaLimit(*args, **kwargs)¶

Bases: ModelNormal

Options for limiting results returned.

Parameters:

count (int, optional) – Number of results to return.
order (QuerySortOrder, optional) – Direction of sort.

widget_formula_style¶

class WidgetFormulaStyle(*args, **kwargs)¶

Bases: ModelNormal

Styling options for widget formulas.

Parameters:

palette (str, optional) – The color palette used to display the formula. A guide to the available color palettes can be found at https://docs.datadoghq.com/dashboards/guide/widget_colors
palette_index (int, optional) – Index specifying which color to use within the palette.

widget_grouping¶

class WidgetGrouping(*args, **kwargs)¶

Bases: ModelSimple

The kind of grouping to use.

Parameters:

value (str) – Must be one of [“check”, “cluster”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_horizontal_align¶

class WidgetHorizontalAlign(*args, **kwargs)¶

Bases: ModelSimple

Horizontal alignment.

Parameters:

value (str) – Must be one of [“center”, “left”, “right”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_image_sizing¶

class WidgetImageSizing(*args, **kwargs)¶

Bases: ModelSimple

How to size the image on the widget. The values are based on the image object-fit CSS properties.: Note: zoom, fit and center values are deprecated.

Parameters:

value (str) – Must be one of [“fill”, “contain”, “cover”, “none”, “scale-down”, “zoom”, “fit”, “center”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_layout¶

class WidgetLayout(*args, **kwargs)¶

Bases: ModelNormal

The layout for a widget on a free or new dashboard layout dashboard.

Parameters:

height (int) – The height of the widget. Should be a non-negative integer.
is_column_break (bool, optional) – Whether the widget should be the first one on the second column in high density or not. Note : Only for the new dashboard layout and only one widget in the dashboard should have this property set to true.
width (int) – The width of the widget. Should be a non-negative integer.
x (int) – The position of the widget on the x (horizontal) axis. Should be a non-negative integer.
y (int) – The position of the widget on the y (vertical) axis. Should be a non-negative integer.

widget_layout_type¶

class WidgetLayoutType(*args, **kwargs)¶

Bases: ModelSimple

Layout type of the group.

Parameters:

value (str) – If omitted defaults to “ordered”. Must be one of [“ordered”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_line_type¶

class WidgetLineType(*args, **kwargs)¶

Bases: ModelSimple

Type of lines displayed.

Parameters:

value (str) – Must be one of [“dashed”, “dotted”, “solid”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_line_width¶

class WidgetLineWidth(*args, **kwargs)¶

Bases: ModelSimple

Width of line displayed.

Parameters:

value (str) – Must be one of [“normal”, “thick”, “thin”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_live_span¶

class WidgetLiveSpan(*args, **kwargs)¶

Bases: ModelSimple

The available timeframes depend on the widget you are using.

Parameters:

value (str) – Must be one of [“1m”, “5m”, “10m”, “15m”, “30m”, “1h”, “4h”, “1d”, “2d”, “1w”, “1mo”, “3mo”, “6mo”, “week_to_date”, “month_to_date”, “1y”, “alert”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_margin¶

class WidgetMargin(*args, **kwargs)¶

Bases: ModelSimple

Size of the margins around the image.: Note: small and large values are deprecated.

Parameters:

value (str) – Must be one of [“sm”, “md”, “lg”, “small”, “large”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_marker¶

class WidgetMarker(*args, **kwargs)¶

Bases: ModelNormal

Markers allow you to add visual conditional formatting for your graphs.

Parameters:

display_type (str, optional) –
Combination of:
- A severity error, warning, ok, or info
- A line type: dashed, solid, or bold In this case of a Distribution widget, this can be set to be x_axis_percentile.
label (str, optional) – Label to display over the marker.
time (str, optional) – Timestamp for the widget.
value (str) – Value to apply. Can be a single value y = 15 or a range of values 0 < y < 10.

widget_message_display¶

class WidgetMessageDisplay(*args, **kwargs)¶

Bases: ModelSimple

Amount of log lines to display

Parameters:

value (str) – Must be one of [“inline”, “expanded-md”, “expanded-lg”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_monitor_summary_display_format¶

class WidgetMonitorSummaryDisplayFormat(*args, **kwargs)¶

Bases: ModelSimple

What to display on the widget.

Parameters:

value (str) – Must be one of [“counts”, “countsAndList”, “list”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_monitor_summary_sort¶

class WidgetMonitorSummarySort(*args, **kwargs)¶

Bases: ModelSimple

Widget sorting methods.

Parameters:

value (str) – Must be one of [“name”, “group”, “status”, “tags”, “triggered”, “group,asc”, “group,desc”, “name,asc”, “name,desc”, “status,asc”, “status,desc”, “tags,asc”, “tags,desc”, “triggered,asc”, “triggered,desc”, “priority,asc”, “priority,desc”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_node_type¶

class WidgetNodeType(*args, **kwargs)¶

Bases: ModelSimple

Which type of node to use in the map.

Parameters:

value (str) – Must be one of [“host”, “container”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_order_by¶

class WidgetOrderBy(*args, **kwargs)¶

Bases: ModelSimple

What to order by.

Parameters:

value (str) – Must be one of [“change”, “name”, “present”, “past”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_palette¶

class WidgetPalette(*args, **kwargs)¶

Bases: ModelSimple

Color palette to apply.

Parameters:

value (str) – Must be one of [“blue”, “custom_bg”, “custom_image”, “custom_text”, “gray_on_white”, “grey”, “green”, “orange”, “red”, “red_on_white”, “white_on_gray”, “white_on_green”, “green_on_white”, “white_on_red”, “white_on_yellow”, “yellow_on_white”, “black_on_light_yellow”, “black_on_light_green”, “black_on_light_red”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_request_style¶

class WidgetRequestStyle(*args, **kwargs)¶

Bases: ModelNormal

Define request widget style.

Parameters:

line_type (WidgetLineType, optional) – Type of lines displayed.
line_width (WidgetLineWidth, optional) – Width of line displayed.
palette (str, optional) – Color palette to apply to the widget.

widget_service_summary_display_format¶

class WidgetServiceSummaryDisplayFormat(*args, **kwargs)¶

Bases: ModelSimple

Number of columns to display.

Parameters:

value (str) – Must be one of [“one_column”, “two_column”, “three_column”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_size_format¶

class WidgetSizeFormat(*args, **kwargs)¶

Bases: ModelSimple

Size of the widget.

Parameters:

value (str) – Must be one of [“small”, “medium”, “large”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_sort¶

class WidgetSort(*args, **kwargs)¶

Bases: ModelSimple

Widget sorting methods.

Parameters:

value (str) – Must be one of [“asc”, “desc”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_style¶

class WidgetStyle(*args, **kwargs)¶

Bases: ModelNormal

Widget style definition.

Parameters:: palette (str, optional) – Color palette to apply to the widget.

widget_summary_type¶

class WidgetSummaryType(*args, **kwargs)¶

Bases: ModelSimple

Which summary type should be used.

Parameters:

value (str) – Must be one of [“monitors”, “groups”, “combined”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_text_align¶

class WidgetTextAlign(*args, **kwargs)¶

Bases: ModelSimple

How to align the text on the widget.

Parameters:

value (str) – Must be one of [“center”, “left”, “right”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_tick_edge¶

class WidgetTickEdge(*args, **kwargs)¶

Bases: ModelSimple

Define how you want to align the text on the widget.

Parameters:

value (str) – Must be one of [“bottom”, “left”, “right”, “top”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_time¶

class WidgetTime(*args, **kwargs)¶

Bases: ModelNormal

Time setting for the widget.

Parameters:: live_span (WidgetLiveSpan, optional) – The available timeframes depend on the widget you are using.

widget_time_windows¶

class WidgetTimeWindows(*args, **kwargs)¶

Bases: ModelSimple

Define a time window.

Parameters:

value (str) – Must be one of [“7d”, “30d”, “90d”, “week_to_date”, “previous_week”, “month_to_date”, “previous_month”, “global_time”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_vertical_align¶

class WidgetVerticalAlign(*args, **kwargs)¶

Bases: ModelSimple

Vertical alignment.

Parameters:

value (str) – Must be one of [“center”, “top”, “bottom”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_view_mode¶

class WidgetViewMode(*args, **kwargs)¶

Bases: ModelSimple

Define how you want the SLO to be displayed.

Parameters:

value (str) – Must be one of [“overall”, “component”, “both”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.

widget_viz_type¶

class WidgetVizType(*args, **kwargs)¶

Bases: ModelSimple

Whether to display the Alert Graph as a timeseries or a top list.

Parameters:

value (str) – Must be one of [“timeseries”, “toplist”].
_check_type (bool) – If True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True.
_path_to_item (tuple/list) – This is a list of keys or values to drill down to the model in received_data when deserializing a response.
_spec_property_naming (bool) – True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default).
_configuration (Configuration) – The instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done.