Amazon SageMaker is a fully-managed service that provides every developer and data scientist with the ability to quickly build, train, and deploy machine learning (ML) models at scale. ML is realized in inference. SageMaker offers four Inference options:

Real-Time Inference
Serverless Inference
Asynchronous Inference
Batch Transform

These four options can be broadly classified into Online and Batch inference options. In Online Inference, requests are expected to be processed as they arrive, and the consuming application expects a response after each request is processed. This can either happen synchronously (real-time Inference, serverless) or asynchronously (asynchronous inference). In a synchronous pattern, the consuming application is blocked and can’t proceed until it receives a response. These workloads tend to be real-time applications, such as online credit card fraud detection, where responses are expected in the order of milliseconds to seconds and request payloads are small (a few

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