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Amazon SageMaker AI adds concurrency sweeps for endpoint right-sizing

Right-size generative AI endpoints with concurrency sweeps on Amazon SageMaker AI

官方一手AWS Machine Learning Blog@Mona Mona
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The CreateAIBenchmarkJob API is available to any SageMaker AI customer, so teams hosting open-source models like Llama can cut inference costs by matching instance types to real traffic instead of over-provisioning.

AWS introduces concurrency sweeps on Amazon SageMaker AI to benchmark generative AI endpoints under increasing load levels. The workflow uses the CreateAIBenchmarkJob API to run automated sweeps against a deployed model. Results give engineers data on throughput and latency at each concurrency level, which informs endpoint instance type and fleet size decisions.

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Right-size generative AI endpoints with concurrency sweeps on Amazon SageMaker AI

Concurrency sweeps help you right-size a generative AI endpoint on Amazon SageMaker AI by systematically benchmarking it at increasing load levels. This post walks through deploying a model, running automated concurrency sweeps with the CreateAIBenchmarkJob API, and using the results to make data-driven capacity decisions about fleet size.

#Amazon SageMaker AI#AWS#benchmarking#builders

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