Pre-check endpoint request and response for tabular data - Amazon SageMaker AI
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Pre-check endpoint request and response for tabular data

We recommend that you deploy your model to a SageMaker AI real-time inference endpoint, and send requests to the endpoint. Manually examine the requests and responses to make sure that both are compliant with the requirements in the Endpoint requests for tabular data section and the Endpoint response for tabular data section. If your model container supports batch requests, you can start with a single record request, and then try two or more records.

The following commands show how to request a response using the Amazon CLI. The Amazon CLI is pre-installed in SageMaker Studio and SageMaker Notebook instances. To install the Amazon CLI, follow this installation guide.

aws sagemaker-runtime invoke-endpoint \
  --endpoint-name $ENDPOINT_NAME \
  --content-type $CONTENT_TYPE \
  --accept $ACCEPT_TYPE \
  --body $REQUEST_DATA \
  $CLI_BINARY_FORMAT \
  /dev/stderr 1>/dev/null

The parameters are defined, as follows.

  • $ENDPOINT NAME – The name of the endpoint.

  • $CONTENT_TYPE – The MIME type of the request (model container input).

  • $ACCEPT_TYPE – The MIME type of the response (model container output).

  • $REQUEST_DATA – The requested payload string.

  • $CLI_BINARY_FORMAT – The format of the command line interface (CLI) parameter. For Amazon CLI v1, this parameter should remain blank. For v2, this parameter should be set to --cli-binary-format raw-in-base64-out.

Note

Amazon CLI v2 passes binary parameters as base64-encoded strings by default.