[TimothyFitz]

By far the easiest way to get similar behavior is to run your Django app via Gunicorn (proxied from Nginx). Gunicorn supports hot code reloading via SIGHUP, and it does so by forking and gracefully killing old processes.

If your requirements don't match gunicorn (not django, not python, etc) then you can use https://github.com/TimothyFitz/zdd a project I wrote to automate rewriting nginx config files to deal with changing proxied portfiles. To integrate any existing server, all you have to do is make it bind to port 0 (let the OS choose a port) and the write a foo.port file that contains the port number (like a pidfile). That's it.

[mattyb]

I mentioned this in a thread the other day; I've yet to see a good use case for hot code reloading. Can you really not drain requests to that host via HAProxy (or similar), and then actually restart the service? The nice thing about that approach is that your choice of service runtime doesn't matter.

[TimothyFitz]

Your method will stall responses for server shutdown + server startup time, which for Ruby/Python apps is usually measured in tens of seconds, and for other web servers can be much worse. Hot code reloading lets you avoid any downtime at all, and with it usually being built into the framework/language specific server you get the functionality "for free".

Zdd (the project I linked to) is all about spawning a new process in parallel. All the advantages of your approach (switch to an entirely different language? Who cares) but without the stalls.

Zdd also lets you keep the old process alive through the duration of the deploy (and after), and with a little work could let you switch back in the event of a bad deploy without having to start the old version up again.

[jonhohle]

The method he's describing requires no downtime or stalled requests. Connections are drained from some pool in a load balance set if servers. The services is restarted with the new code. The hosts are given traffic again once the are initialized and healthy.

The advantages to this method include being completely platform agnostic, as well as giving you a window to verify successful update without worrying about production traffic.

[TimothyFitz]

Thanks for the clarification. The downsides to that approach are that you need multiple machines, and the duration of your deploys is much longer. Not to mention, you'd have to script a deploy process across multiple machines (which is not easy, in the way that "SIGHUP Gunicorn" is easy).

Personally I've found the "put new instances into a load balancer" method to make more sense for system changes (packages, kernels, OS versions) where deploying the change is inherently slow or expensive, but the method doesn't make sense for code deploys where deploy time is important.

[nja]

Thanks for the Gunicorn hot-reloading tip. I've been using Gunicorn with Supervisor, and I wish I'd known about the SIGHUP trick earlier.