Changes This feature helps you monitor model performance characteristics such as accuracy, identify undesired bias in your ML models, and explain model decisions better with explainability drift detection.
Changes You can now specify the production variant to send the inference request to, when invoking a SageMaker Endpoint that is running two or more variants.
Changes Amazon SageMaker now supports multi-model endpoints to host multiple models on an endpoint using a single inference container.
Changes SageMaker Runtime supports CustomAttributes header which allows customers provide additional information in a request for an inference submitted to a model or in the response about the inference returned by a model hosted at an Amazon SageMaker endpoint.
Changes Amazon SageMaker is a fully-managed service that enables data scientists and developers to quickly and easily build, train, and deploy machine learning models, at scale.