Enhance your existing machine learning (ML) workflow by integrating with SageMaker model training features while preserving the rest of your custom serverless endpoints with Fargate. This reference architecture illustrates how to integrate SageMaker with other compute services when you do not use SageMaker for your full ML lifecycle. Fargate lets you maintain a serverless approach while enabling a higher memory model and concurrency limits with no changes to your code.
