interface PredictiveScalingPredefinedMetricPairProperty
| Language | Type name |
|---|---|
.NET | Amazon.CDK.AWS.ApplicationAutoScaling.CfnScalingPolicy.PredictiveScalingPredefinedMetricPairProperty |
Go | github.com/aws/aws-cdk-go/awscdk/v2/awsapplicationautoscaling#CfnScalingPolicy_PredictiveScalingPredefinedMetricPairProperty |
Java | software.amazon.awscdk.services.applicationautoscaling.CfnScalingPolicy.PredictiveScalingPredefinedMetricPairProperty |
Python | aws_cdk.aws_applicationautoscaling.CfnScalingPolicy.PredictiveScalingPredefinedMetricPairProperty |
TypeScript | aws-cdk-lib » aws_applicationautoscaling » CfnScalingPolicy » PredictiveScalingPredefinedMetricPairProperty |
Represents a metric pair for a predictive scaling policy.
The following predefined metrics are available for predictive scaling:
ECSServiceAverageCPUUtilizationECSServiceAverageMemoryUtilizationECSServiceCPUUtilizationECSServiceMemoryUtilizationECSServiceTotalCPUUtilizationECSServiceTotalMemoryUtilizationALBRequestCountALBRequestCountPerTargetTotalALBRequestCount
Example
// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import { aws_applicationautoscaling as appscaling } from 'aws-cdk-lib';
const predictiveScalingPredefinedMetricPairProperty: appscaling.CfnScalingPolicy.PredictiveScalingPredefinedMetricPairProperty = {
predefinedMetricType: 'predefinedMetricType',
// the properties below are optional
resourceLabel: 'resourceLabel',
};
Properties
| Name | Type | Description |
|---|---|---|
| predefined | string | Indicates which metrics to use. |
| resource | string | A label that uniquely identifies a specific target group from which to determine the total and average request count. |
predefinedMetricType
Type:
string
Indicates which metrics to use.
There are two different types of metrics for each metric type: one is a load metric and one is a scaling metric.
resourceLabel?
Type:
string
(optional)
A label that uniquely identifies a specific target group from which to determine the total and average request count.

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