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To build integration between SageMaker endpoints and Kinesis Data Application use this blog - https://aws.amazon.com/blogs/architecture/realtime-in-stream-inference-kinesis-sagemaker-flink/. It help to setup serverless service to invoke the SageMaker inference endpoint.
To use batching. The Tensorflow documentation mentions the following:
- This link mentions that you can include multiple instances in your predict request (or multiple examples in classify/regress requests) to get multiple prediction results in one request to your Endpoint.
- This link mentions that you can configure SageMaker TensorFlow Serving Container to batch multiple records together before performing an inference
You would still have to handle the logic internally in ECS/Lambda to control how many records you consume from your stream in one batch, but at least you will be able to infer on the whole batch on the SageMaker endpoint end based on the above.
answered 4 years ago
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