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PutAnomalyDetectorInput

Source code in docs_src/capo_cloudwatch/types/put_anomaly_detector_input.py
class PutAnomalyDetectorInput(TypedDict, closed=True):
    namespace: NotRequired["capo_cloudwatch.types.namespace.Namespace"]
    """<p>The namespace of the metric to create the anomaly detection model for.</p>"""
    metric_name: NotRequired["capo_cloudwatch.types.metric_name.MetricName"]
    """<p>The name of the metric to create the anomaly detection model for.</p>"""
    dimensions: NotRequired["capo_cloudwatch.types.dimensions.Dimensions"]
    """<p>The metric dimensions to create the anomaly detection model for.</p>"""
    stat: NotRequired[
        "capo_cloudwatch.types.anomaly_detector_metric_stat.AnomalyDetectorMetricStat"
    ]
    """<p>The statistic to use for the metric and the anomaly detection model.</p>"""
    configuration: NotRequired[
        "capo_cloudwatch.types.anomaly_detector_configuration.AnomalyDetectorConfiguration"
    ]
    """<p>The configuration specifies details about how the anomaly detection model is to be trained, including time ranges to exclude when training and updating the model. You can specify as many as 10 time ranges.</p> <p>The configuration can also include the time zone to use for the metric.</p>"""
    metric_characteristics: NotRequired[
        "capo_cloudwatch.types.metric_characteristics.MetricCharacteristics"
    ]
    """<p>Use this object to include parameters to provide information about your metric to CloudWatch to help it build more accurate anomaly detection models. Currently, it includes the <code>PeriodicSpikes</code> parameter.</p>"""
    single_metric_anomaly_detector: NotRequired[
        "capo_cloudwatch.types.single_metric_anomaly_detector.SingleMetricAnomalyDetector"
    ]
    """<p>A single metric anomaly detector to be created.</p> <p>When using <code>SingleMetricAnomalyDetector</code>, you cannot include the following parameters in the same operation:</p> <ul> <li> <p> <code>Dimensions</code> </p> </li> <li> <p> <code>MetricName</code> </p> </li> <li> <p> <code>Namespace</code> </p> </li> <li> <p> <code>Stat</code> </p> </li> <li> <p>the <code>MetricMathAnomalyDetector</code> parameters of <code>PutAnomalyDetectorInput</code> </p> </li> </ul> <p>Instead, specify the single metric anomaly detector attributes as part of the property <code>SingleMetricAnomalyDetector</code>.</p>"""
    metric_math_anomaly_detector: NotRequired[
        "capo_cloudwatch.types.metric_math_anomaly_detector.MetricMathAnomalyDetector"
    ]
    """<p>The metric math anomaly detector to be created.</p> <p>When using <code>MetricMathAnomalyDetector</code>, you cannot include the following parameters in the same operation:</p> <ul> <li> <p> <code>Dimensions</code> </p> </li> <li> <p> <code>MetricName</code> </p> </li> <li> <p> <code>Namespace</code> </p> </li> <li> <p> <code>Stat</code> </p> </li> <li> <p>the <code>SingleMetricAnomalyDetector</code> parameters of <code>PutAnomalyDetectorInput</code> </p> </li> </ul> <p>Instead, specify the metric math anomaly detector attributes as part of the property <code>MetricMathAnomalyDetector</code>.</p>"""

configuration instance-attribute

configuration: NotRequired[AnomalyDetectorConfiguration]

The configuration specifies details about how the anomaly detection model is to be trained, including time ranges to exclude when training and updating the model. You can specify as many as 10 time ranges.

The configuration can also include the time zone to use for the metric.

dimensions instance-attribute

dimensions: NotRequired[Dimensions]

The metric dimensions to create the anomaly detection model for.

metric_characteristics instance-attribute

metric_characteristics: NotRequired[MetricCharacteristics]

Use this object to include parameters to provide information about your metric to CloudWatch to help it build more accurate anomaly detection models. Currently, it includes the PeriodicSpikes parameter.

metric_math_anomaly_detector instance-attribute

metric_math_anomaly_detector: NotRequired[MetricMathAnomalyDetector]

The metric math anomaly detector to be created.

When using MetricMathAnomalyDetector, you cannot include the following parameters in the same operation:

  • Dimensions

  • MetricName

  • Namespace

  • Stat

  • the SingleMetricAnomalyDetector parameters of PutAnomalyDetectorInput

Instead, specify the metric math anomaly detector attributes as part of the property MetricMathAnomalyDetector.

metric_name instance-attribute

metric_name: NotRequired[MetricName]

The name of the metric to create the anomaly detection model for.

namespace instance-attribute

namespace: NotRequired[Namespace]

The namespace of the metric to create the anomaly detection model for.

single_metric_anomaly_detector instance-attribute

single_metric_anomaly_detector: NotRequired[SingleMetricAnomalyDetector]

A single metric anomaly detector to be created.

When using SingleMetricAnomalyDetector, you cannot include the following parameters in the same operation:

  • Dimensions

  • MetricName

  • Namespace

  • Stat

  • the MetricMathAnomalyDetector parameters of PutAnomalyDetectorInput

Instead, specify the single metric anomaly detector attributes as part of the property SingleMetricAnomalyDetector.

stat instance-attribute

stat: NotRequired[AnomalyDetectorMetricStat]

The statistic to use for the metric and the anomaly detection model.