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Why Your Async Python Services Crash Under AI Load (And How to Build a Real Production Inference Pipeline)

This story is from 2026-09-04. It is preserved in the archive; the latest stories are on the live feed.

When a software engineer builds a prototype for an AI microservice using FastAPI, asyncio, and PyTorch or Hugging Face, everything runs smoothly on a local environment. But as soon as the service hits production and faces thousands of concurrent requests, performance degrades rapidly: ​Latency spik…

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  1. 2026-09-04 05:06 · DEV Community — AI
    Why Your Async Python Services Crash Under AI Load (And How to Build a Real Production Inference Pipeline)

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