RandomCutForestConfiguration
Configuration for the Random Cut Forest algorithm used for anomaly detection in time-series data.
Contents
- query
-
The Prometheus query used to retrieve the time-series data for anomaly detection.
Important
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, andsum.Type: String
Length Constraints: Minimum length of 1. Maximum length of 8192.
Required: Yes
- ignoreNearExpectedFromAbove
-
Configuration for ignoring values that are near expected values from above during anomaly detection.
Type: IgnoreNearExpected object
Note: This object is a Union. Only one member of this object can be specified or returned.
Required: No
- ignoreNearExpectedFromBelow
-
Configuration for ignoring values that are near expected values from below during anomaly detection.
Type: IgnoreNearExpected object
Note: This object is a Union. Only one member of this object can be specified or returned.
Required: No
- sampleSize
-
The number of data points sampled from the input stream for the Random Cut Forest algorithm. The default number is 256 consecutive data points.
Type: Integer
Valid Range: Minimum value of 256. Maximum value of 1024.
Required: No
- shingleSize
-
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.
Type: Integer
Valid Range: Minimum value of 2. Maximum value of 1024.
Required: No
See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following:
