CfnAnomalyDetectorProps
- class aws_cdk.aws_cloudwatch.CfnAnomalyDetectorProps(*, configuration=None, dimensions=None, metric_math_anomaly_detector=None, metric_name=None, namespace=None, single_metric_anomaly_detector=None, stat=None)
Bases:
object
Properties for defining a
CfnAnomalyDetector
.- Parameters:
configuration (
Union
[IResolvable
,ConfigurationProperty
,Dict
[str
,Any
],None
]) – Specifies details about how the anomaly detection model is to be trained, including time ranges to exclude when training and updating the model. The configuration can also include the time zone to use for the metric.dimensions (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,DimensionProperty
,Dict
[str
,Any
]]],None
]) – The dimensions of the metric associated with the anomaly detection band.metric_math_anomaly_detector (
Union
[IResolvable
,MetricMathAnomalyDetectorProperty
,Dict
[str
,Any
],None
]) – The CloudWatch metric math expression for this anomaly detector.metric_name (
Optional
[str
]) – The name of the metric associated with the anomaly detection band.namespace (
Optional
[str
]) – The namespace of the metric associated with the anomaly detection band.single_metric_anomaly_detector (
Union
[IResolvable
,SingleMetricAnomalyDetectorProperty
,Dict
[str
,Any
],None
]) – The CloudWatch metric and statistic for this anomaly detector.stat (
Optional
[str
]) – The statistic of the metric associated with the anomaly detection band.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_cloudwatch as cloudwatch cfn_anomaly_detector_props = cloudwatch.CfnAnomalyDetectorProps( configuration=cloudwatch.CfnAnomalyDetector.ConfigurationProperty( excluded_time_ranges=[cloudwatch.CfnAnomalyDetector.RangeProperty( end_time="endTime", start_time="startTime" )], metric_time_zone="metricTimeZone" ), dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty( name="name", value="value" )], metric_math_anomaly_detector=cloudwatch.CfnAnomalyDetector.MetricMathAnomalyDetectorProperty( metric_data_queries=[cloudwatch.CfnAnomalyDetector.MetricDataQueryProperty( id="id", # the properties below are optional account_id="accountId", expression="expression", label="label", metric_stat=cloudwatch.CfnAnomalyDetector.MetricStatProperty( metric=cloudwatch.CfnAnomalyDetector.MetricProperty( metric_name="metricName", namespace="namespace", # the properties below are optional dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty( name="name", value="value" )] ), period=123, stat="stat", # the properties below are optional unit="unit" ), period=123, return_data=False )] ), metric_name="metricName", namespace="namespace", single_metric_anomaly_detector=cloudwatch.CfnAnomalyDetector.SingleMetricAnomalyDetectorProperty( dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty( name="name", value="value" )], metric_name="metricName", namespace="namespace", stat="stat" ), stat="stat" )
Attributes
- configuration
Specifies details about how the anomaly detection model is to be trained, including time ranges to exclude when training and updating the model.
The configuration can also include the time zone to use for the metric.
- dimensions
The dimensions of the metric associated with the anomaly detection band.
- metric_math_anomaly_detector
The CloudWatch metric math expression for this anomaly detector.
- metric_name
The name of the metric associated with the anomaly detection band.
- namespace
The namespace of the metric associated with the anomaly detection band.
- single_metric_anomaly_detector
The CloudWatch metric and statistic for this anomaly detector.
- stat
The statistic of the metric associated with the anomaly detection band.