AnomalyDetector

An anomaly detection model associated with a particular CloudWatch metric, statistic, or metric math expression. You can use the model to display a band of expected, normal values when the metric is graphed.

If you have enabled unified cross-account observability, and this account is a monitoring account, the metric can be in the same account or a source account.

Configuration

The configuration specifies details about how the anomaly detection model is to be trained, including time ranges to exclude from use for training the model, and the time zone to use for the metric.

Type: AnomalyDetectorConfiguration object

Required: No

Dimensions.member.N

This member has been deprecated.

The metric dimensions associated with the anomaly detection model.

Type: Array of Dimension objects

Array Members: Maximum number of 30 items.

Required: No

MetricCharacteristics

This object includes parameters that you can use to provide information about your metric to CloudWatch to help it build more accurate anomaly detection models. Currently, it includes the PeriodicSpikes parameter.

Type: MetricCharacteristics object

Required: No

MetricMathAnomalyDetector

The CloudWatch metric math expression for this anomaly detector.

Type: MetricMathAnomalyDetector object

Required: No

MetricName

This member has been deprecated.

The name of the metric associated with the anomaly detection model.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 255.

Required: No

Namespace

This member has been deprecated.

The namespace of the metric associated with the anomaly detection model.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 255.

Pattern: [^:].*

Required: No

SingleMetricAnomalyDetector

The CloudWatch metric and statistic for this anomaly detector.

Type: SingleMetricAnomalyDetector object

Required: No

Stat

This member has been deprecated.

The statistic associated with the anomaly detection model.

Type: String

Length Constraints: Maximum length of 50.

Pattern: (SampleCount|Average|Sum|Minimum|Maximum|IQM|(p|tc|tm|ts|wm)(\d{1,2}(\.\d{0,10})?|100)|[ou]\d+(\.\d*)?)(_E|_L|_H)?|(TM|TC|TS|WM)\(((((\d{1,2})(\.\d{0,10})?|100(\.0{0,10})?)%)?:((\d{1,2})(\.\d{0,10})?|100(\.0{0,10})?)%|((\d{1,2})(\.\d{0,10})?|100(\.0{0,10})?)%:(((\d{1,2})(\.\d{0,10})?|100(\.0{0,10})?)%)?)\)|(TM|TC|TS|WM|PR)\(((\d+(\.\d{0,10})?|(\d+(\.\d{0,10})?[Ee][+-]?\d+)):((\d+(\.\d{0,10})?|(\d+(\.\d{0,10})?[Ee][+-]?\d+)))?|((\d+(\.\d{0,10})?|(\d+(\.\d{0,10})?[Ee][+-]?\d+)))?:(\d+(\.\d{0,10})?|(\d+(\.\d{0,10})?[Ee][+-]?\d+)))\)

Required: No

StateValue

The current status of the anomaly detector's training.

Type: String

Valid Values: PENDING_TRAINING | TRAINED_INSUFFICIENT_DATA | TRAINED

Required: No

AnomalyDetector

Contents

See Also