AWS API Changes

2025/10/30 - Amazon Prometheus Service - 5 new api methods

Changes Add Anomaly Detection APIs for Amazon Managed Prometheus

PutAnomalyDetector (new)

Link ¶

When you call PutAnomalyDetector, the operation creates a new anomaly detector if one doesn't exist, or updates an existing one. Each call to this operation triggers a complete retraining of the detector, which includes querying the minimum required samples and backfilling the detector with historical data. This process occurs regardless of whether you're making a minor change like updating the evaluation interval or making more substantial modifications. The operation serves as the single method for creating, updating, and retraining anomaly detectors.

See also: AWS API Documentation

Request Syntax

client.put_anomaly_detector(
    workspaceId='string',
    anomalyDetectorId='string',
    evaluationIntervalInSeconds=123,
    missingDataAction={
        'markAsAnomaly': True|False,
        'skip': True|False
    },
    configuration={
        'randomCutForest': {
            'query': 'string',
            'shingleSize': 123,
            'sampleSize': 123,
            'ignoreNearExpectedFromAbove': {
                'amount': 123.0,
                'ratio': 123.0
            },
            'ignoreNearExpectedFromBelow': {
                'amount': 123.0,
                'ratio': 123.0
            }
        }
    },
    labels={
        'string': 'string'
    },
    clientToken='string'
)

type workspaceId:

string

param workspaceId:

[REQUIRED]

The identifier of the workspace containing the anomaly detector to update.

type anomalyDetectorId:

string

param anomalyDetectorId:

[REQUIRED]

The identifier of the anomaly detector to update.

type evaluationIntervalInSeconds:

integer

param evaluationIntervalInSeconds:

The frequency, in seconds, at which the anomaly detector evaluates metrics.

type missingDataAction:

dict

param missingDataAction:

Specifies the action to take when data is missing during evaluation.

markAsAnomaly (boolean) --

Marks missing data points as anomalies.
skip (boolean) --

Skips evaluation when data is missing.

type configuration:

dict

param configuration:

[REQUIRED]

The algorithm configuration for the anomaly detector.

randomCutForest (dict) --

The Random Cut Forest algorithm configuration for anomaly detection.
- query (string) -- [REQUIRED]
  
  The Prometheus query used to retrieve the time-series data for anomaly detection.
  
  Warning
  
  Random Cut Forest queries must be wrapped by a supported PromQL aggregation operator. For more information, see Aggregation operators on the Prometheus docs website.
  
  Supported PromQL aggregation operators: avg, count, group, max, min, quantile, stddev, stdvar, and sum.
- shingleSize (integer) --
  
  The number of consecutive data points used to create a shingle for the Random Cut Forest algorithm. The default number is 8 consecutive data points.
- sampleSize (integer) --
  
  The number of data points sampled from the input stream for the Random Cut Forest algorithm. The default number is 256 consecutive data points.
- ignoreNearExpectedFromAbove (dict) --
  
  Configuration for ignoring values that are near expected values from above during anomaly detection.
  
  Note
  
  This is a Tagged Union structure. Only one of the following top level keys can be set: amount, ratio.
  - amount (float) --
    
    The absolute amount by which values can differ from expected values before being considered anomalous.
  - ratio (float) --
    
    The ratio by which values can differ from expected values before being considered anomalous.
- ignoreNearExpectedFromBelow (dict) --
  
  Configuration for ignoring values that are near expected values from below during anomaly detection.
  
  Note
  
  This is a Tagged Union structure. Only one of the following top level keys can be set: amount, ratio.
  - amount (float) --
    
    The absolute amount by which values can differ from expected values before being considered anomalous.
  - ratio (float) --
    
    The ratio by which values can differ from expected values before being considered anomalous.

type labels:

dict

param labels:

The Amazon Managed Service for Prometheus metric labels to associate with the anomaly detector.

(string) --
- (string) --

type clientToken:

string

param clientToken:

A unique, case-sensitive identifier that you provide to ensure the idempotency of the request.

This field is autopopulated if not provided.

rtype:

dict

returns:

Response Syntax

{
    'anomalyDetectorId': 'string',
    'arn': 'string',
    'status': {
        'statusCode': 'CREATING'|'ACTIVE'|'UPDATING'|'DELETING'|'CREATION_FAILED'|'UPDATE_FAILED'|'DELETION_FAILED',
        'statusReason': 'string'
    },
    'tags': {
        'string': 'string'
    }
}

Response Structure

(dict) --
- anomalyDetectorId (string) --
  
  The unique identifier of the updated anomaly detector.
- arn (string) --
  
  The Amazon Resource Name (ARN) of the updated anomaly detector.
- status (dict) --
  
  The status information of the updated anomaly detector.
  - statusCode (string) --
    
    The status code of the anomaly detector.
  - statusReason (string) --
    
    A description of the current status of the anomaly detector.
- tags (dict) --
  
  The tags applied to the updated anomaly detector.
  - (string) --
    
    The key of the tag. Must not begin with aws:.
    - (string) --
      
      The value of the tag.

DeleteAnomalyDetector (new)

Link ¶

Removes an anomaly detector from a workspace. This operation is idempotent.

See also: AWS API Documentation

Request Syntax

client.delete_anomaly_detector(
    workspaceId='string',
    anomalyDetectorId='string',
    clientToken='string'
)

type workspaceId:

string

param workspaceId:

[REQUIRED]

The identifier of the workspace containing the anomaly detector to delete.

type anomalyDetectorId:

string

param anomalyDetectorId:

[REQUIRED]

The identifier of the anomaly detector to delete.

type clientToken:

string

param clientToken:

A unique, case-sensitive identifier that you provide to ensure the idempotency of the request.

This field is autopopulated if not provided.

returns:

None

DescribeAnomalyDetector (new)

Link ¶

Retrieves detailed information about a specific anomaly detector, including its status and configuration.

See also: AWS API Documentation

Request Syntax

client.describe_anomaly_detector(
    workspaceId='string',
    anomalyDetectorId='string'
)

type workspaceId:

string

param workspaceId:

[REQUIRED]

The identifier of the workspace containing the anomaly detector.

type anomalyDetectorId:

string

param anomalyDetectorId:

[REQUIRED]

The identifier of the anomaly detector to describe.

rtype:

dict

returns:

Response Syntax

{
    'anomalyDetector': {
        'arn': 'string',
        'anomalyDetectorId': 'string',
        'alias': 'string',
        'evaluationIntervalInSeconds': 123,
        'missingDataAction': {
            'markAsAnomaly': True|False,
            'skip': True|False
        },
        'configuration': {
            'randomCutForest': {
                'query': 'string',
                'shingleSize': 123,
                'sampleSize': 123,
                'ignoreNearExpectedFromAbove': {
                    'amount': 123.0,
                    'ratio': 123.0
                },
                'ignoreNearExpectedFromBelow': {
                    'amount': 123.0,
                    'ratio': 123.0
                }
            }
        },
        'labels': {
            'string': 'string'
        },
        'status': {
            'statusCode': 'CREATING'|'ACTIVE'|'UPDATING'|'DELETING'|'CREATION_FAILED'|'UPDATE_FAILED'|'DELETION_FAILED',
            'statusReason': 'string'
        },
        'createdAt': datetime(2015, 1, 1),
        'modifiedAt': datetime(2015, 1, 1),
        'tags': {
            'string': 'string'
        }
    }
}

Response Structure

(dict) --
- anomalyDetector (dict) --
  
  The detailed information about the anomaly detector.
  - arn (string) --
    
    The Amazon Resource Name (ARN) of the anomaly detector.
  - anomalyDetectorId (string) --
    
    The unique identifier of the anomaly detector.
  - alias (string) --
    
    The user-friendly name of the anomaly detector.
  - evaluationIntervalInSeconds (integer) --
    
    The frequency, in seconds, at which the anomaly detector evaluates metrics.
  - missingDataAction (dict) --
    
    The action taken when data is missing during evaluation.
    Note
    
    This is a Tagged Union structure. Only one of the following top level keys will be set: markAsAnomaly, skip. If a client receives an unknown member it will set SDK_UNKNOWN_MEMBER as the top level key, which maps to the name or tag of the unknown member. The structure of SDK_UNKNOWN_MEMBER is as follows:
```
'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}
```
    - markAsAnomaly (boolean) --
      
      Marks missing data points as anomalies.
    - skip (boolean) --
      
      Skips evaluation when data is missing.
  - configuration (dict) --
    
    The algorithm configuration of the anomaly detector.
    Note
    
    This is a Tagged Union structure. Only one of the following top level keys will be set: randomCutForest. If a client receives an unknown member it will set SDK_UNKNOWN_MEMBER as the top level key, which maps to the name or tag of the unknown member. The structure of SDK_UNKNOWN_MEMBER is as follows:
```
'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}
```
    - randomCutForest (dict) --
      
      The Random Cut Forest algorithm configuration for anomaly detection.
      - query (string) --
        
        The Prometheus query used to retrieve the time-series data for anomaly detection.
        
        Warning
        
        Random Cut Forest queries must be wrapped by a supported PromQL aggregation operator. For more information, see Aggregation operators on the Prometheus docs website.
        
        Supported PromQL aggregation operators: avg, count, group, max, min, quantile, stddev, stdvar, and sum.
      - shingleSize (integer) --
        
        The number of consecutive data points used to create a shingle for the Random Cut Forest algorithm. The default number is 8 consecutive data points.
      - sampleSize (integer) --
        
        The number of data points sampled from the input stream for the Random Cut Forest algorithm. The default number is 256 consecutive data points.
      - ignoreNearExpectedFromAbove (dict) --
        
        Configuration for ignoring values that are near expected values from above during anomaly detection.
        
        Note
        
        This is a Tagged Union structure. Only one of the following top level keys will be set: amount, ratio. If a client receives an unknown member it will set SDK_UNKNOWN_MEMBER as the top level key, which maps to the name or tag of the unknown member. The structure of SDK_UNKNOWN_MEMBER is as follows:
        
        'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}
        
        amount (float) --
        
        The absolute amount by which values can differ from expected values before being considered anomalous.
        
        ratio (float) --
        
        The ratio by which values can differ from expected values before being considered anomalous.
      - ignoreNearExpectedFromBelow (dict) --
        
        Configuration for ignoring values that are near expected values from below during anomaly detection.
        
        Note
        
        This is a Tagged Union structure. Only one of the following top level keys will be set: amount, ratio. If a client receives an unknown member it will set SDK_UNKNOWN_MEMBER as the top level key, which maps to the name or tag of the unknown member. The structure of SDK_UNKNOWN_MEMBER is as follows:
        
        'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}
        
        amount (float) --
        
        The absolute amount by which values can differ from expected values before being considered anomalous.
        
        ratio (float) --
        
        The ratio by which values can differ from expected values before being considered anomalous.
  - labels (dict) --
    
    The Amazon Managed Service for Prometheus metric labels associated with the anomaly detector.
    - (string) --
      - (string) --
  - status (dict) --
    
    The current status of the anomaly detector.
    - statusCode (string) --
      
      The status code of the anomaly detector.
    - statusReason (string) --
      
      A description of the current status of the anomaly detector.
  - createdAt (datetime) --
    
    The timestamp when the anomaly detector was created.
  - modifiedAt (datetime) --
    
    The timestamp when the anomaly detector was last modified.
  - tags (dict) --
    
    The tags applied to the anomaly detector.
    - (string) --
      
      The key of the tag. Must not begin with aws:.
      - (string) --
        
        The value of the tag.

CreateAnomalyDetector (new)

Link ¶

Creates an anomaly detector within a workspace using the Random Cut Forest algorithm for time-series analysis. The anomaly detector analyzes Amazon Managed Service for Prometheus metrics to identify unusual patterns and behaviors.

See also: AWS API Documentation

Request Syntax

client.create_anomaly_detector(
    workspaceId='string',
    alias='string',
    evaluationIntervalInSeconds=123,
    missingDataAction={
        'markAsAnomaly': True|False,
        'skip': True|False
    },
    configuration={
        'randomCutForest': {
            'query': 'string',
            'shingleSize': 123,
            'sampleSize': 123,
            'ignoreNearExpectedFromAbove': {
                'amount': 123.0,
                'ratio': 123.0
            },
            'ignoreNearExpectedFromBelow': {
                'amount': 123.0,
                'ratio': 123.0
            }
        }
    },
    labels={
        'string': 'string'
    },
    clientToken='string',
    tags={
        'string': 'string'
    }
)

type workspaceId:

string

param workspaceId:

[REQUIRED]

The identifier of the workspace where the anomaly detector will be created.

type alias:

string

param alias:

[REQUIRED]

A user-friendly name for the anomaly detector.

type evaluationIntervalInSeconds:

integer

param evaluationIntervalInSeconds:

The frequency, in seconds, at which the anomaly detector evaluates metrics. The default value is 60 seconds.

type missingDataAction:

dict

param missingDataAction:

Specifies the action to take when data is missing during evaluation.

markAsAnomaly (boolean) --

Marks missing data points as anomalies.
skip (boolean) --

Skips evaluation when data is missing.

type configuration:

dict

param configuration:

[REQUIRED]

The algorithm configuration for the anomaly detector.

randomCutForest (dict) --

The Random Cut Forest algorithm configuration for anomaly detection.
- query (string) -- [REQUIRED]
  
  The Prometheus query used to retrieve the time-series data for anomaly detection.
  
  Warning
  
  Random Cut Forest queries must be wrapped by a supported PromQL aggregation operator. For more information, see Aggregation operators on the Prometheus docs website.
  
  Supported PromQL aggregation operators: avg, count, group, max, min, quantile, stddev, stdvar, and sum.
- shingleSize (integer) --
  
  The number of consecutive data points used to create a shingle for the Random Cut Forest algorithm. The default number is 8 consecutive data points.
- sampleSize (integer) --
  
  The number of data points sampled from the input stream for the Random Cut Forest algorithm. The default number is 256 consecutive data points.
- ignoreNearExpectedFromAbove (dict) --
  
  Configuration for ignoring values that are near expected values from above during anomaly detection.
  
  Note
  
  This is a Tagged Union structure. Only one of the following top level keys can be set: amount, ratio.
  - amount (float) --
    
    The absolute amount by which values can differ from expected values before being considered anomalous.
  - ratio (float) --
    
    The ratio by which values can differ from expected values before being considered anomalous.
- ignoreNearExpectedFromBelow (dict) --
  
  Configuration for ignoring values that are near expected values from below during anomaly detection.
  
  Note
  
  This is a Tagged Union structure. Only one of the following top level keys can be set: amount, ratio.
  - amount (float) --
    
    The absolute amount by which values can differ from expected values before being considered anomalous.
  - ratio (float) --
    
    The ratio by which values can differ from expected values before being considered anomalous.

type labels:

dict

param labels:

The Amazon Managed Service for Prometheus metric labels to associate with the anomaly detector.

(string) --
- (string) --

type clientToken:

string

param clientToken:

A unique, case-sensitive identifier that you provide to ensure the idempotency of the request.

This field is autopopulated if not provided.

type tags:

dict

param tags:

The metadata to apply to the anomaly detector to assist with categorization and organization.

(string) --

The key of the tag. Must not begin with aws:.
- (string) --
  
  The value of the tag.

rtype:

dict

returns:

Response Syntax

{
    'anomalyDetectorId': 'string',
    'arn': 'string',
    'status': {
        'statusCode': 'CREATING'|'ACTIVE'|'UPDATING'|'DELETING'|'CREATION_FAILED'|'UPDATE_FAILED'|'DELETION_FAILED',
        'statusReason': 'string'
    },
    'tags': {
        'string': 'string'
    }
}

Response Structure

(dict) --
- anomalyDetectorId (string) --
  
  The unique identifier of the created anomaly detector.
- arn (string) --
  
  The Amazon Resource Name (ARN) of the created anomaly detector.
- status (dict) --
  
  The status information of the created anomaly detector.
  - statusCode (string) --
    
    The status code of the anomaly detector.
  - statusReason (string) --
    
    A description of the current status of the anomaly detector.
- tags (dict) --
  
  The tags applied to the created anomaly detector.
  - (string) --
    
    The key of the tag. Must not begin with aws:.
    - (string) --
      
      The value of the tag.

ListAnomalyDetectors (new)

Link ¶

Returns a paginated list of anomaly detectors for a workspace with optional filtering by alias.

See also: AWS API Documentation

Request Syntax

client.list_anomaly_detectors(
    workspaceId='string',
    alias='string',
    maxResults=123,
    nextToken='string'
)

type workspaceId:

string

param workspaceId:

[REQUIRED]

The identifier of the workspace containing the anomaly detectors to list.

type alias:

string

param alias:

Filters the results to anomaly detectors with the specified alias.

type maxResults:

integer

param maxResults:

The maximum number of results to return in a single call. Valid range is 1 to 1000.

type nextToken:

string

param nextToken:

The pagination token to continue retrieving results.

rtype:

dict

returns:

Response Syntax

{
    'anomalyDetectors': [
        {
            'arn': 'string',
            'anomalyDetectorId': 'string',
            'alias': 'string',
            'status': {
                'statusCode': 'CREATING'|'ACTIVE'|'UPDATING'|'DELETING'|'CREATION_FAILED'|'UPDATE_FAILED'|'DELETION_FAILED',
                'statusReason': 'string'
            },
            'createdAt': datetime(2015, 1, 1),
            'modifiedAt': datetime(2015, 1, 1),
            'tags': {
                'string': 'string'
            }
        },
    ],
    'nextToken': 'string'
}

Response Structure

(dict) --
- anomalyDetectors (list) --
  
  The list of anomaly detectors in the workspace.
  - (dict) --
    
    Summary information about an anomaly detector for list operations.
    - arn (string) --
      
      The Amazon Resource Name (ARN) of the anomaly detector.
    - anomalyDetectorId (string) --
      
      The unique identifier of the anomaly detector.
    - alias (string) --
      
      The user-friendly name of the anomaly detector.
    - status (dict) --
      
      The current status of the anomaly detector.
      - statusCode (string) --
        
        The status code of the anomaly detector.
      - statusReason (string) --
        
        A description of the current status of the anomaly detector.
    - createdAt (datetime) --
      
      The timestamp when the anomaly detector was created.
    - modifiedAt (datetime) --
      
      The timestamp when the anomaly detector was last modified.
    - tags (dict) --
      
      The tags applied to the anomaly detector.
      - (string) --
        
        The key of the tag. Must not begin with aws:.
        
        (string) --
        
        The value of the tag.
- nextToken (string) --
  
  The pagination token to retrieve the next set of results.