gunicorn VS copilot-cli

I'm hoping so – gunicorn has a long-open pull request that would fix `--reuse-port`, which currently does nothing

https://github.com/benoitc/gunicorn/pull/2938

However, I'm curious about the best way to deploy, specifically with regard to WSGI. I've tried using the raw eventlet WSGI server (`eventlet.wsgi.server(eventlet.listen(("", 8000)), application)`). I then start it with `python manage.py runserver`. This has worked okay, but I'm unsure about how scalable it is. It seems like the standard stack is Django + Gunicorn + NGINX. Based on `python-socketio` documentation, this should be possible. I tried django + eventlet + gunicorn, but it seems like gunicorn a) [doesn't play nice with eventlet](https://github.com/benoitc/gunicorn/pull/2581) and b) only supports one worker. Gevent + Gunicorn doesn't have this bug, but still only supports one worker. Also, I'm not sure how actively maintained gevent is. So I'm not sure how scalable either Gunicorn + eventlet or Gunicorn + geventlet is as a WSGI server. So I'm not sure if Gunicorn is my best bet, or if it's too limited.

For building your API, I recommend using the Flask library. It is very beginner-friendly, and you will be able to build a simple API in a matter of minutes! Keep in mind that, for a more serious project, you should definitely use something like gunicorn to run you API as a production server.

Interesting looks like it might actually be a python bug. Somehow just changing from sys.exit(0) -> os._exit(0) apparently fixes it.

https://github.com/benoitc/gunicorn/pull/2820

The cool thing is that you can easily migrate your WSGI- application such as Flask, Django, or Gunicorn to AWS.

Yeah, that's kind of the impression I was getting. I stumbled across a github issue for gunicorn along these lines.

Taking a glimpse at gunicorn's code it looks like they pretty much all do the same: 2. seems to be creating a wsgi app using django's internals, and 3. uses 2.

AWS Copilot CLI is an open source command line interface for running containers on AWS App Runner, Amazon Elastic Container Service (ECS), and AWS Fargate.

sudo curl -Lo /usr/local/bin/copilot https://github.com/aws/copilot-cli/releases/latest/download/copilot-linux && sudo chmod +x /usr/local/bin/copilot

Check out AWS Copilot CLI: https://aws.github.io/copilot-cli/

This is by far the best way to deploy compute into AWS in containerized workloads.

The abstraction you want is Jobs: ttps://aws.github.io/copilot-cli/docs/concepts/jobs/

Building this any other way on AWS would require provisioning multiple artifacts. The Copilot Jobs abstraction basically encapsulates the provisioning of those artifacts into one repeatable pattern.

AWS Copilot CLI is a tool that lets you deploy production-ready, scalable services on AWS from a Dockerfile in one command.

and here is the copilot page if you are interested https://aws.github.io/copilot-cli/

For larger high availability required things, AWS ECS with RDS, ElastiCache, CloudFront, S3, etc.. Really like Copilot for deployment/env/secret/sidecar management (probably needs a rename now): https://aws.github.io/copilot-cli/

We are spending about 60% less. Workload has actually lessened since AWS is so much more stable. Getting to a similar DX as Heroku was quite the lift, but once it's done, it's done. These days we generally only have outages when we screw something up ourselves. I recommend https://github.com/aws/copilot-cli for starting out on ECS.

I'd recommend checking out AWS Copilot (https://aws.github.io/copilot-cli/)