Clean up - Amazon SageMaker AI
Delete a scaling policyDeregister a model

Clean up

After you have finished using autoscaling for your serverless endpoint with Provisioned Concurrency, you should clean up the resources you created. This involves deleting the scaling policy and deregistering the model from Application Auto Scaling. Cleaning up ensures that you don't incur unnecessary costs for resources you're no longer using.

Delete a scaling policy

You can delete a scaling policy with the AWS Management Console, the AWS CLI, or the Application Auto Scaling API. For more information on deleting a scaling policy with the AWS Management Console, see Delete a scaling policy in the SageMaker AI autoscaling documentation.

Delete a scaling policy (AWS CLI)

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

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

  • --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/MyEndpoint/variant/MyVariant.

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

  • --scalable-dimension – Set this value to sagemaker:variant:DesiredProvisionedConcurrency.

The following example deletes scaling policy named MyScalingPolicy from a model named MyVariant. 

aws application-autoscaling delete-scaling-policy \
    --policy-name MyScalingPolicy \
    --service-namespace sagemaker \
    --scalable-dimension sagemaker:variant:DesiredProvisionedConcurrency \
    --resource-id endpoint/MyEndpoint/variant/MyVariant

Delete a scaling policy (Application Auto Scaling API)

To delete a scaling policy to your model, use the DeleteScalingPolicy Application Auto Scaling API action with the following parameters:

  • PolicyName – The name of the scaling policy.

  • 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/MyEndpoint/variant/MyVariant.

  • ServiceNamespace – Set this value to sagemaker.

  • ScalableDimension – Set this value to sagemaker:variant:DesiredProvisionedConcurrency.

The following example uses the Application Auto Scaling API to delete a scaling policy named MyScalingPolicy from a model named MyVariant. 

POST / HTTP/1.1
Host: autoscaling.us-east-2.amazonaws.com
Accept-Encoding: identity
X-Amz-Target: AnyScaleFrontendService.DeleteScalingPolicy
X-Amz-Date: 20160506T182145Z
User-Agent: aws-cli/1.10.23 Python/2.7.11 Darwin/15.4.0 botocore/1.4.8
Content-Type: application/x-amz-json-1.1
Authorization: AUTHPARAMS

{
    "PolicyName": "MyScalingPolicy",
    "ServiceNamespace": "sagemaker",
    "ResourceId": "endpoint/MyEndpoint/variant/MyVariant",
    "ScalableDimension": "sagemaker:variant:DesiredProvisionedConcurrency",
}

Deregister a model

You can deregister a model with the AWS Management Console, the AWS CLI, or the Application Auto Scaling API.

Deregister a model (AWS CLI)

To deregister a model from Application Auto Scaling, use the deregister-scalable-target AWS CLI; command with the following parameters:

  • --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/MyEndpoint/variant/MyVariant.

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

  • --scalable-dimension – Set this value to sagemaker:variant:DesiredProvisionedConcurrency.

The following example deregisters a model named MyVariant from Application Auto Scaling. 

aws application-autoscaling deregister-scalable-target \
    --service-namespace sagemaker \
    --scalable-dimension sagemaker:variant:DesiredProvisionedConcurrency \
    --resource-id endpoint/MyEndpoint/variant/MyVariant

Deregister a model (Application Auto Scaling API)

To deregister a model from Application Auto Scaling use the DeregisterScalableTarget Application Auto Scaling API action with the following parameters:

  • 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/MyEndpoint/variant/MyVariant.

  • ServiceNamespace – Set this value to sagemaker.

  • ScalableDimension – Set this value to sagemaker:variant:DesiredProvisionedConcurrency.

The following example uses the Application Auto Scaling API to deregister a model named MyVariant from Application Auto Scaling. 

POST / HTTP/1.1
Host: autoscaling.us-east-2.amazonaws.com
Accept-Encoding: identity
X-Amz-Target: AnyScaleFrontendService.DeregisterScalableTarget
X-Amz-Date: 20160506T182145Z
User-Agent: aws-cli/1.10.23 Python/2.7.11 Darwin/15.4.0 botocore/1.4.8
Content-Type: application/x-amz-json-1.1
Authorization: AUTHPARAMS

{
    "ServiceNamespace": "sagemaker",
    "ResourceId": "endpoint/MyEndpoint/variant/MyVariant",
    "ScalableDimension": "sagemaker:variant:DesiredProvisionedConcurrency",
}

Deregister a model (AWS Management Console)

To deregister a model (production variant) with the AWS Management Console:

  1. Open the Amazon SageMaker AI console.

  2. In the navigational panel, choose Inference.

  3. Choose Endpoints to view a list of your endpoints.

  4. Choose the serverless endpoint hosting the production variant. A page with the settings of the endpoint will appear, with the production variants listed under Endpoint runtime settings section.

  5. Select the production variant that you want to deregister, and choose Configure auto scaling. The Configure variant automatic scaling dialog box appears.

  6. Choose Deregister auto scaling.