I would consider the following optimizations first before attempting to rewrite an HTTP API since you already did the hard part:
1. For multiples processes use `gunicorn` [1]. Runs your app across multiple processes without you having to touch your code much. It's the same as having the n instances of the same backend app where n being the number of CPU cores you're willing to throw at it. One backend process per core, full isolation.
2. For multiple threads use `gunicorn` + `gevent` workers [2]. Provides multiprocessing + multithreaded functionality out of the box if you have IO intensive. It's not perfect but works very well in some situations.
3. Lastly, if CPU is where you have a bottleneck, that means you have some memory to spare (even if it's not much). Throw some LRU cache or cachetools [3] over functions that return the same result or functions that do expensive I/O.
1. For multiples processes use `gunicorn` [1]. Runs your app across multiple processes without you having to touch your code much. It's the same as having the n instances of the same backend app where n being the number of CPU cores you're willing to throw at it. One backend process per core, full isolation.
2. For multiple threads use `gunicorn` + `gevent` workers [2]. Provides multiprocessing + multithreaded functionality out of the box if you have IO intensive. It's not perfect but works very well in some situations.
3. Lastly, if CPU is where you have a bottleneck, that means you have some memory to spare (even if it's not much). Throw some LRU cache or cachetools [3] over functions that return the same result or functions that do expensive I/O.
[1]: https://www.joelsleppy.com/blog/gunicorn-sync-workers/
[2]: https://www.joelsleppy.com/blog/gunicorn-async-workers-with-...
[3]: https://pypi.org/project/cachetools/