Right-size generative AI endpoints with concurrency sweeps on Amazon SageMaker AI | Amazon Web Services
Concurrency sweeps help you right-size a generative AI endpoint by finding the instance type and serving configuration that maximizes price-performance while holding latency within acceptable bounds. Without a systematic approach, right-sizing means deploying, load-testing manually, adjusting, and repeating until the numbers look acceptable. Choose five ml.g7e.2xlarge instances when one would suffice, and you burn your budget on idle GPUs. Choose too few, and requests queue, latency spikes, and users experience degraded service.
Concurrency sweeps address this problem. A concurrency sweep is a systematic benchmarking approach that sends controlled, increasing levels of concurrent traffic to your Amazon SageMaker AI endpoint and analyzes its performance. Concurrency sweeps are built into Amazon SageMaker AI Inference Recommendations, so there’s no custom load-testing infrastructure to build or maintain.
In this post, we walk through deploying the NVIDIA Nemotron-3 Nano 30Bmodel, running automated concurrency sweeps, and using the results to make data-driven capacity decisions....
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