Register a model - Amazon SageMaker AI
Register a model (AWS CLI)Register a model (Application Auto Scaling API)

Register a model

Before you add a scaling policy to your model, you first must register your model for auto scaling and define the scaling limits for the model.

The following procedures cover how to register a model (production variant) for auto scaling using the AWS Command Line Interface (AWS CLI) or Application Auto Scaling API.

Register a model (AWS CLI)

To register your production variant, use the register-scalable-target command with the following parameters:

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

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

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

  • --min-capacity—The minimum number of instances. This value must be set to at least 1 and must be equal to or less than the value specified for max-capacity.

  • --max-capacity—The maximum number of instances. This value must be set to at least 1 and must be equal to or greater than the value specified for min-capacity.

The following example shows how to register a variant named my-variant, running on the my-endpoint endpoint, that can be dynamically scaled to have one to eight instances.

aws application-autoscaling register-scalable-target \
  --service-namespace sagemaker \
  --resource-id endpoint/my-endpoint/variant/my-variant \
  --scalable-dimension sagemaker:variant:DesiredInstanceCount \
  --min-capacity 1 \
  --max-capacity 8

Register a model (Application Auto Scaling API)

To register your model with Application Auto Scaling, use the RegisterScalableTarget Application Auto Scaling API action with the following parameters:

  • ServiceNamespace—Set this value to sagemaker.

  • ResourceID—The resource identifier for the production 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.

  • MinCapacity—The minimum number of instances. This value must be set to at least 1 and must be equal to or less than the value specified for MaxCapacity.

  • MaxCapacity—The maximum number of instances. This value must be set to at least 1 and must be equal to or greater than the value specified for MinCapacity.

The following example shows how to register a variant named my-variant, running on the my-endpoint endpoint, that can be dynamically scaled to use one to eight instances.

POST / HTTP/1.1
Host: application-autoscaling.us-east-2.amazonaws.com
Accept-Encoding: identity
X-Amz-Target: AnyScaleFrontendService.RegisterScalableTarget
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

{
    "ServiceNamespace": "sagemaker",
    "ResourceId": "endpoint/my-endpoint/variant/my-variant",
    "ScalableDimension": "sagemaker:variant:DesiredInstanceCount",
    "MinCapacity": 1,
    "MaxCapacity": 8
}