AILAB Track 4: Production ML Serving with FastAPI & Docker

01 / Why a student should open this

Packaging ML models into low-latency async REST microservices, writing Pydantic validation schemas, and containerizing with multi-stage Dockerfiles.

02 / Student Context & Field Notes

Best for

Final stage deployment for AILAB projects

Time commitment

1 week

Prerequisites

Python type hints and async/await basics.

Best part / timestamp

Automatic OpenAPI docs at /docs makes testing endpoints immediate.

Watch out / Caveat

Do not load large PyTorch models inside every request handler; load once at lifespan startup.

Personal note from contributor

“This is what separates a student Jupyter notebook from a hireable junior engineer.”

https://fastapi.tiangolo.com/tutorial/