Amazon SageMaker AI Async Inference Now Supports Inline Request Payloads
Decision Brief
What changedAmazon SageMaker AI Async Inference now allows sending inference payloads directly in the InvokeEndpointAsync API request body, eliminating the need to upload to Amazon S3 first.
Why it mattersAI builders need to know this simplifies the inference request flow and improves efficiency.
Who should careTeams building on model APIs
Affected stackNo specific stack identified
Builder actionMonitor
Source confidenceHigh · Official release / blog / repo
Amazon SageMaker AI Async Inference now supports inline request payloads, enabling users to send inference payloads directly in the InvokeEndpointAsync API request body. This feature removes the step of uploading input data to Amazon Simple Storage Service (Amazon S3) before each invocation, simplifying the inference process and enhancing usability.
Summary basis: official / RSS sourceUnless it says 'full article read', this summary is based only on publicly available content — it never pretends to have read restricted originals.
Sources
- AWS：Machine Learning Blog
Applied ML, infra, and deployment guidance useful for AI builders on AWS.
- AWS：Machine Learning Blog