Invoke a serverless endpoint - Amazon SageMaker AI
To invoke an endpoint

Invoke a serverless endpoint

In order to perform inference using a serverless endpoint, you must send an HTTP request to the endpoint. You can use the InvokeEndpoint API or the AWS CLI, which make a POST request to invoke your endpoint. The maximum request and response payload size for serverless invocations is 4 MB. For serverless endpoints:

  • The model must download and the server must respond successfully to /ping within 3 minutes.

  • The timeout for the container to respond to inference requests to /invocations is 1 minute.

To invoke an endpoint

The following example uses the AWS SDK for Python (Boto3) to call the InvokeEndpoint API. Note that unlike the other API calls in this guide, for InvokeEndpoint, you must use SageMaker Runtime Runtime as the client. Specify the following values:

  • For endpoint_name, use the name of the in-service serverless endpoint you want to invoke.

  • For content_type, specify the MIME type of your input data in the request body (for example, application/json).

  • For payload, use your request payload for inference. Your payload should be in bytes or a file-like object.

runtime = boto3.client("sagemaker-runtime")

endpoint_name = "<your-endpoint-name>"
content_type = "<request-mime-type>"
payload = <your-request-body>

response = runtime.invoke_endpoint(
    EndpointName=endpoint_name,
    ContentType=content_type,
    Body=payload
)