Sagemaker Asynchronous Endpoint Configuration

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We deployed a LighGBM Regression model and endpoint using Sagemaker Jumpstart. We have attempted to configure this endpoint as 'asynchronous' via the console. Receiving Error: ValidationException-Network Isolation is not supported when specifying an AsyncInferenceConfig.

Looking at the model's network details the model has Enable Network Isolation set as 'True'. This was default output setting set by JumpStart.

How can we diasble Network Isolation to in order to make this endpoint asynchronous?

1 Answer
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Accepted Answer

Vanilla SageMaker "Models" (as opposed to versioned ModelPackages) are immutable in the API with no "UpdateModel" action... But I think you should be able to create a new Model copying the settings of the current one.

I'd suggest to:

  1. Use DescribeModel (via boto3.client("sagemaker").describe_model(), assuming you're using Python) to fetch all the parameters of the existing JumpStart model such as the S3 artifact location and other settings
  2. Use CreateModel (create_model()) to create a new model with same configuration but network isolation disabled
  3. Use your new model to try and deploy an async endpoint

Probably you'd find the low-level boto3 SDK more intuitive for this task than the high-level sagemaker SDK's Model class - because the latter does some magic that makes typical build/train/deploy workflows easier but can be less natural for hacking around with existing model definitions. For example, creating an SMSDK Model object doesn't actually create a Model in the SageMaker API, because deployment instance type affects choice of container image so that gets deferred until a .deploy() call or similar later.

AWS
EXPERT
Alex_T
answered 2 years ago

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