Use `gunicorn` instead `uvicorn` in main

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Example Code

import uvicorn

os.environ["TOKENIZERS_PARALLELISM"] = "false"


if __name__ == "__main__":
    uvicorn.run("start:app",
                host="0.0.0.0",
                port=8080,
                workers=2,
                limit_concurrency=70,
                backlog=300
                )

Description

I have an app using uvicorn and I have problems with accumulating memory usage. In addition, inside the app itself i use multiprocessing.Process to execute model inference using tensorflow in parallel processes. I have tried many configurations and settings on uvicorn but the memory leak issue persists. At the moment I think that this is due to the thread handling done by uvicorn. I got a suggestion to use gunicorn instead of uvocorn, but I am not sure how I could simply switch from one to another, programmatically. The application is working, and returning the requests, there are no error messages. In the documentation the examples use uvicorn - can gunicorn be used just the same way as uvicorn in the examples? My question is: would a switch from uvicorn to gunicorn make sense, and if so, would that impact the fastapi application?

Operating System

Linux

Operating System Details

Ubuntu 20.04 python3.7

pip packages: fastapi==0.61.1 fastapi-route-logger-middleware==0.1.3 grpcio==1.32.0 joblib==0.17.0 numpy==1.18.5 optional.py==1.1.0 pandas==0.25.3 prometheus-fastapi-instrumentator==5.7.1 pydantic==1.7.1 python-multipart==0.0.5 tensorflow-gpu==2.3.2 uvicorn==0.12.2

FastAPI Version

fastapi==0.61.1

Python Version

Python 3.7.12

Additional Context

The application is used for implementing prediction using 3 tensorflow models. Two of which are run inside a multiproessing.process call, to achieve parallel execution.

[Kludex]

For those arriving later, Sebastián just updated the docs: https://fastapi.tiangolo.com/deployment/server-workers/

[Kludex]

Yeah… I’m going to talk to the maintainers to see if they can improve this on uvicorn. 😓