Table Of Contents

Feedback

User Guide

First time using the AWS CLI? See the User Guide for help getting started.

Note: You are viewing the documentation for an older major version of the AWS CLI (version 1).

AWS CLI version 2, the latest major version of AWS CLI, is now stable and recommended for general use. To view this page for the AWS CLI version 2, click here. For more information see the AWS CLI version 2 installation instructions and migration guide.

[ aws . sagemaker-runtime ]

invoke-endpoint-async

Description

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 in an asynchronous manner.

Inference requests sent to this API are enqueued for asynchronous processing. The processing of the inference request may or may not complete before the you receive a response from this API. The response from this API will not contain the result of the inference request but contain information about where you can locate it.

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

See also: AWS API Documentation

See 'aws help' for descriptions of global parameters.

Synopsis

  invoke-endpoint-async
--endpoint-name <value>
[--content-type <value>]
[--accept <value>]
[--custom-attributes <value>]
[--inference-id <value>]
--input-location <value>
[--request-ttl-seconds <value>]
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]

Options

--endpoint-name (string)

The name of the endpoint that you specified when you created the endpoint using the ` CreateEndpoint https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html`__ API.

--content-type (string)

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

--accept (string)

The desired MIME type of the inference in the response.

--custom-attributes (string)

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).

The code in your model is responsible for setting or updating any custom attributes in the response. If your code does not set this value in the response, an empty value is returned. For example, if a custom attribute represents the trace ID, your model can prepend the custom attribute with Trace ID : in your post-processing function.

This feature is currently supported in the AWS SDKs but not in the Amazon SageMaker Python SDK.

--inference-id (string)

The identifier for the inference request. Amazon SageMaker will generate an identifier for you if none is specified.

--input-location (string)

The Amazon S3 URI where the inference request payload is stored.

--request-ttl-seconds (integer)

Maximum age in seconds a request can be in the queue before it is marked as expired.

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See 'aws help' for descriptions of global parameters.

Output

InferenceId -> (string)

Identifier for an inference request. This will be the same as the InferenceId specified in the input. Amazon SageMaker will generate an identifier for you if you do not specify one.

OutputLocation -> (string)

The Amazon S3 URI where the inference response payload is stored.