There's also the process worker pool model, in which a master process forks a number of worker processes to handle all requests. Unicorn (for Ruby) does things

There's also the process worker pool model, in which a master process forks a number of worker processes to handle all requests. Unicorn (for Ruby) does things this way...in part because when it was released, Rails apps couldn't handle multithreading all that well. I think Ruby also had some trouble with it, so this was just the easiest/most predictable way of getting good performance out of your Rails app. Originally, the way `php-fpm` works is pretty much how the entire web worked. Every request into a server would go through `inetd`, it would fork a handler process, and the request would respond when the process exited. This became very difficult to handle at scale, mostly because of the overhead for forking a process, so the next logical step is to have a pool of worker processes ready to go in order to immediately receive requests. This is great for applications that don't need to get redeployed very often, but as we moved into more of a continuous deployment workflow, it began to break down as worker processes would need to be restarted, going back to that whole "overhead" thing. Unicorn suffers from this problem a bit, if you try to `SIGHUP` and reload application code when workers are still processing requests, Unicorn will wait until those processes have finished responding to restart the process and load the new version. If a client is taking too long and hanging onto the process, it's very possible that the process will just never reload the code and you'll have weird errors happening every so often. A solution to this problem is to move this pool of worker processes into a pool of threads, which allow the server to control a bit more about how the application code is reloaded, and not have to deal with the overhead of forking processes. I believe that's how NGINX, Node.js, Puma, et. al. work under the hood...there's a thread pool of workers and another thread that listens to requests. Everything is event-driven, so when a new event comes in, the listener thread just sends that event off to the pool of worker threads. Basically the same idea, but using an event loop as a model for better concurrency support. (Puma is a bit different because it does allow for worker processes in addition to threads, but this isn't necessary, it just allows for better performance on larger machines)