Amazon SageMaker
Developer Guide

InvokeEndpoint

After you deploy a model into production using Amazon SageMaker hosting services, your client applications use this API to get inferences from the model hosted at the specified endpoint.

For an overview of Amazon SageMaker, see How It Works.

Amazon SageMaker strips all POST headers except those supported by the API. Amazon SageMaker might add additional headers. You should not rely on the behavior of headers outside those enumerated in the request syntax.

Calls to InvokeEndpoint are authenticated by using AWS Signature Version 4. For information, see Authenticating Requests (AWS Signature Version 4) in the Amazon S3 API Reference.

A customer's model containers must respond to requests within 60 seconds. The model itself can have a maximum processing time of 60 seconds before responding to the /invocations. If your model is going to take 50-60 seconds of processing time, the SDK socket timeout should be set to be 70 seconds.

Note

Endpoints are scoped to an individual account, and are not public. The URL does not contain the account ID, but Amazon SageMaker determines the account ID from the authentication token that is supplied by the caller.

Request Syntax

POST /endpoints/EndpointName/invocations HTTP/1.1 Content-Type: ContentType Accept: Accept X-Amzn-SageMaker-Custom-Attributes: CustomAttributes Body

URI Request Parameters

The request requires the following URI parameters.

Accept

The desired MIME type of the inference in the response.

Length Constraints: Maximum length of 1024.

Pattern: \p{ASCII}*

ContentType

The MIME type of the input data in the request body.

Length Constraints: Maximum length of 1024.

Pattern: \p{ASCII}*

CustomAttributes

Provides additional information about a request for an inference submitted to a model hosted at an Amazon SageMaker endpoint. The information is an opaque value that is forwarded verbatim. You could use this value, for example, to provide an ID that you can use to track a request or to provide other metadata that a service endpoint was programmed to process. The value must consist of no more than 1024 visible US-ASCII characters as specified in Section 3.3.6. Field Value Components of the Hypertext Transfer Protocol (HTTP/1.1). This feature is currently supported in the AWS SDKs but not in the Amazon SageMaker Python SDK.

Length Constraints: Maximum length of 1024.

Pattern: \p{ASCII}*

EndpointName

The name of the endpoint that you specified when you created the endpoint using the CreateEndpoint API.

Length Constraints: Maximum length of 63.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9])*

Request Body

The request accepts the following binary data.

Body

Provides input data, in the format specified in the ContentType request header. Amazon SageMaker passes all of the data in the body to the model.

For information about the format of the request body, see Common Data Formats—Inference.

Length Constraints: Maximum length of 5242880.

Response Syntax

HTTP/1.1 200 Content-Type: ContentType x-Amzn-Invoked-Production-Variant: InvokedProductionVariant X-Amzn-SageMaker-Custom-Attributes: CustomAttributes Body

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The response returns the following HTTP headers.

ContentType

The MIME type of the inference returned in the response body.

Length Constraints: Maximum length of 1024.

Pattern: \p{ASCII}*

CustomAttributes

Provides additional information in the response about the inference returned by a model hosted at an Amazon SageMaker endpoint. The information is an opaque value that is forwarded verbatim. You could use this value, for example, to return an ID received in the CustomAttributes header of a request or other metadata that a service endpoint was programmed to produce. The value must consist of no more than 1024 visible US-ASCII characters as specified in Section 3.3.6. Field Value Components of the Hypertext Transfer Protocol (HTTP/1.1). This feature is currently supported in the AWS SDKs but not in the Amazon SageMaker Python SDK.

Length Constraints: Maximum length of 1024.

Pattern: \p{ASCII}*

InvokedProductionVariant

Identifies the production variant that was invoked.

Length Constraints: Maximum length of 1024.

Pattern: \p{ASCII}*

The response returns the following as the HTTP body.

Body

Includes the inference provided by the model.

For information about the format of the response body, see Common Data Formats—Inference.

Length Constraints: Maximum length of 5242880.

Errors

For information about the errors that are common to all actions, see Common Errors.

InternalFailure

An internal failure occurred.

HTTP Status Code: 500

ModelError

Model (owned by the customer in the container) returned an error 500.

HTTP Status Code: 424

ServiceUnavailable

The service is unavailable. Try your call again.

HTTP Status Code: 503

ValidationError

Inspect your request and try again.

HTTP Status Code: 400

Example

Pass a trace ID in the CustomAttribute of a request and return it in the CustomAttribute of the response.

In this example a trace ID is passed to the service endpoint in the CustomAttributes header of the request and then retrieved and returned in the CustomAttributes header of the response.

Sample Request

import boto3 client = boto3.client('sagemaker-runtime') custom_attributes = "c000b4f9-df62-4c85-a0bf-7c525f9104a4" # An example of a trace ID. endpoint_name = "..." # Your endpoint name. content_type = "..." # The MIME type of the input data in the request body. accept = "..." # The desired MIME type of the inference in the response. payload = "..." # Payload for inference.

Sample Response

response = client.invoke_endpoint( EndpointName=endpoint_name, CustomAttributes=custom_attributes, ContentType=content_type, Accept=accept, Body=payload ) print(response['CustomAttributes']) # If model receives and updates the custom_attributes header # by adding "Trace id: " in front of custom_attributes in the request, # custom_attributes in response becomes # "Trace ID: c000b4f9-df62-4c85-a0bf-7c525f9104a4"

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: