Apply a scaling policy - Amazon SageMaker AI
Apply a target tracking scaling policy (AWS CLI)Apply a scaling policy (Application Auto Scaling API)

Apply a scaling policy

After you register your model and define a scaling policy, apply the scaling policy to the registered model. This section shows how to apply a scaling policy using the the AWS Command Line Interface (AWS CLI) or the Application Auto Scaling API.

Apply a target tracking scaling policy (AWS CLI)

To apply a scaling policy to your model, use the put-scaling-policy AWS CLI command with the following parameters:

  • --policy-name—The name of the scaling policy.

  • --policy-type—Set this value to TargetTrackingScaling.

  • --resource-id—The resource identifier for the variant. For this parameter, the resource type is endpoint and the unique identifier is the name of the variant. For example, endpoint/my-endpoint/variant/my-variant.

  • --service-namespace—Set this value to sagemaker.

  • --scalable-dimension—Set this value to sagemaker:variant:DesiredInstanceCount.

  • --target-tracking-scaling-policy-configuration—The target-tracking scaling policy configuration to use for the model.

The following example applies a target tracking scaling policy named my-scaling-policy to a variant named my-variant, running on the my-endpoint endpoint. For the --target-tracking-scaling-policy-configuration option, specify the config.json file that you created previously. 

aws application-autoscaling put-scaling-policy \
  --policy-name my-scaling-policy \
  --policy-type TargetTrackingScaling \
  --resource-id endpoint/my-endpoint/variant/my-variant \
  --service-namespace sagemaker \
  --scalable-dimension sagemaker:variant:DesiredInstanceCount \
  --target-tracking-scaling-policy-configuration file://config.json

Apply a scaling policy (Application Auto Scaling API)

To apply a scaling policy to a variant with the Application Auto Scaling API, use the PutScalingPolicy Application Auto Scaling API action with the following parameters:

  • PolicyName—The name of the scaling policy.

  • ServiceNamespace—Set this value to sagemaker.

  • ResourceID—The resource identifier for the variant. For this parameter, the resource type is endpoint and the unique identifier is the name of the variant. For example, endpoint/my-endpoint/variant/my-variant.

  • ScalableDimension—Set this value to sagemaker:variant:DesiredInstanceCount.

  • PolicyType—Set this value to TargetTrackingScaling.

  • TargetTrackingScalingPolicyConfiguration—The target-tracking scaling policy configuration to use for the variant.

The following example applies a target tracking scaling policy named my-scaling-policy to a variant named my-variant, running on the my-endpoint endpoint. The policy configuration keeps the average invocations per instance at 70.

POST / HTTP/1.1
Host: application-autoscaling.us-east-2.amazonaws.com
Accept-Encoding: identity
X-Amz-Target: AnyScaleFrontendService.
X-Amz-Date: 20230506T182145Z
User-Agent: aws-cli/2.0.0 Python/3.7.5 Windows/10 botocore/2.0.0dev4
Content-Type: application/x-amz-json-1.1
Authorization: AUTHPARAMS

{
    "PolicyName": "my-scaling-policy",
    "ServiceNamespace": "sagemaker",
    "ResourceId": "endpoint/my-endpoint/variant/my-variant",
    "ScalableDimension": "sagemaker:variant:DesiredInstanceCount",
    "PolicyType": "TargetTrackingScaling",
    "TargetTrackingScalingPolicyConfiguration": {
        "TargetValue": 70.0,
        "PredefinedMetricSpecification":
        {
            "PredefinedMetricType": "SageMakerVariantInvocationsPerInstance"
        }
    }
}