Tornado: FriendFeed's non-blocking Python web server is now open source

If you ran a single CherryPy instance, I don't see how that is possible. The Python global interpreter lock prevents a single process from making use of multiple cores.

I implemented the same idea in Ruby event machine: http://gist.github.com/184760

Obviously missing features (auth, nicks, scrolling) but that can all be added in a few mins.

I'd say it's a little more similar to Thin, which is a web server based on EM.

Port: http://gist.github.com/184760

Apache/mod_wsgi creates multiple processes (or can). The issue is that Facebook didn't tell us what configuration settings they used. Did they limit the number of processes? Did they not have it start up enough at the start?

It's clear that Facebook wasn't using a single Apache/mod_wsgi process because that wouldn't get close to 2,000 requests per second. I'm sure they gave it the number of processes that were appropriate for the amount of RAM on the box - the issue is that every Apache process (of which I'm sure they dozens if not hundreds) uses up memory.

It's hard to set that up properly and that's what makes benchmarking so hard. Still, it's not hard to believe that with the weight of Apache in the process, there's going to be at least 5MB of overhead for every request. If you were saving that 5MB of RAM per client times the 2,223 requests per second, that's 11GB worth of freed RAM per second. Let's say Django uses 10MB of RAM for a request: that's an extra 50% increase in capacity right there just by eliminating the 5MB Apache process overhead. And Apache tends to be on the heavier side (5MB is somewhat low as an estimate) and if you can do it asynchronously, you're not tying up RAM as you wait for clients, so you do well.

Now, put Apache/mod_wsgi behind nginx (as a proxy) and you'll also see an increase in requests per second because you won't be tying up all that RAM as a client is downloading and only use the RAM while actually doing work in Python freeing that memory to be used elsewhere. However, I'm guessing that they ran this benchmark locally and so the network tying up Apache instances wasn't a factor.

Clearly, benchmarks are benchmarks, but it isn't as if Facebook and FriendFeed don't have lots of smart engineers and they wouldn't be using their own server if Apache was significantly better. They have a site of massive scale and know how to benchmark things since you need objective data to make decisions based on rather than the religious arguments some get into.

I'd guess that, if one could get Django running under Tornado, it would run similarly and that it's more of Apache being the bottleneck/RAM hog.