Amazon SageMaker Autopilot model deployment - Amazon SageMaker

Amazon SageMaker Autopilot model deployment

To deploy the model that produced the best validation metric in an Autopilot experiment, you have several options. When using Autopilot in SageMaker Studio, you can deploy the model automatically or manually. When working in another development, you can call Autopilot APIs directly to deploy a model.

  • Automatically: To automatically deploy the best model from an Autopilot experiment to an endpoint, accept the default Auto deploy value On when creating the experiment in SageMaker Studio.

    
            Select Decide to use automatic deployment..
    Note

    Automatic deployment will fail if the default resource quota or your customer quota for endpoint instances in a Region are too limited. Currently the requirement is that you need have at least two ml.m5.2xlarge instances. The eu-north-1 Region (Stockholm) does not meet this requirement, for example. The supported instance types for this Region are listed at SageMaker Instance Types in EU (Stockholm) eu-north-1. If you encounter this issue, you can request a service limit increase for SageMaker endpoints instances by following the procedure at Supported Regions and Quotas. In the Case details panel, select SageMaker Endpoints for the Limit type. For Request1, select:

    • Region: EU (Stockholm)

    • Resource Type: SageMaker Hosting

    • Limit: ml.m5.2xlarge (at least)

    • New limit value: 2

  • Manually: To manually deploy the best model from an Autopilot experiment to an endpoint, set the Auto deploy value to Off when creating the experiment in SageMaker Studio.

    
            Select Decide to use automatic deployment..
  • API calls: Make the following series of API calls:

The automatic deployment for the results of an experiment in SageMaker Studio calls the six APIs listed in this last option by default. For information on how to create an experiment, see Create an Amazon SageMaker Autopilot experiment.

Note

To avoid incurring unnecessary charges, delete the endpoints and resources that were created when deploying the model after they are no longer needed. Information on pricing of instances by Region is available at Amazon SageMaker Pricing.