My Summer of (Open) Source

The last few months have been an great experience for me. I’m a graduate student from Potsdam, Germany. However, as some of you might already know, I’m also rather active in the Ruby community. This past year, I had an amazing opportunity.

Engine Yard sponsors a couple of Open Source developers to work full time on their projects. When I asked Dr. Nic Williams whether they would sponsor me spending three months in Portland, working together with Brian Ford on Rubinius, I expected nothing but a no. Turns out, Engine Yard was at least as thrilled about this idea as I was. A few days ago, I finally got back to Germany, and I wanted to give you a quick overview of what I’ve been working on during my time overseas.Like many others, I started contributing to Rubinius a while ago. However, I never really dared to play with the internals. So, my first stop was the Rubinius compiler. To make sure I really understood it and that it’s as flexible as it claims to be, I wrote a Smalltalk implementation using the Rubinius compiler infrastructure and looked into improving its API.

It’s a fun thing to do, as the Rubinius compiler is written entirely in Ruby. And, since Rubinius is bootstrapped, it also runs on other Ruby implementations. That is how you usually install Rubinius: You load the compiler from CRuby, it then compiles the compiler to Rubinius bytecode. If you want to look into this, there is some excellent documentation available on the Rubinius website.

This bytecode can then be executed by the Virtual Machine, which was my next stop. It took me a while to fully understand how things work within the VM. It is actually the only major part of Rubinius not written in Ruby, and the main reason for it’s blazing performance and excellent memory footprint. I am planning ton writing another blog post, or possibly even a series of blog posts about these internals.

Apart from bug fixes and API improvements, I used the gained knowledge to fix, for instance, one of Ruby’s least known and most confusing feature: the implemented flip-flops.

The last thing I worked on was Puma, a new web server for Rails/Rack/Sinatra applications. Rubinius 2.0 is about to be released, fully able to make the best use of all your CPUs. However, most web servers used for deploying Ruby applications are actually single-threaded. Since there is no real threaded option that is still maintained and not JRuby specific, Evan Phoenix and I started working on a new server.

Like many other servers, it uses the rapid HTTP parser that comes with Mongrel. It also uses a dynamically sized thread-pool for processing requests in parallel. With Puma, you now have a go to choice when it comes to deploying web applications on Rubinius. And since it does not contain any Rubinius specific code, it also works quite well on JRuby or CRuby.

To make sure we are heading in the right direction, I started working on a tool for benchmarking web applications under realistic load. The main issue with just using ab, the standard solution for measuring HTTP performance, is that it results in unrealistic numbers both on JRuby and Rubinius. When using ab, you just send the same request over and over again, causing the JIT and code inliner to highly optimize for exactly that request. This usually doesn’t reflect the actual production behavior, though. I therefore wrote code simulating a real browser session and, of course, running multiple of these sessions in parallel.

You think that’s all? Far from it! The Engine Yard OSS Community Grant Program enabled me to speak at six different conferences all over America. At Rocky Mountain Ruby, RubyConf Brazil and RubyConf Uruguay, I gave a talk on “Real Time Rack”. In San Francisco, at GoGaRuCo, I gave a presentation about “Smalltalk On Rubinius - or How To Implement Your Own Programming Language”. At this past year’s RubyConf in New Orleans, I spoke about “Message in a Bottle” and last but not least I gave a presentation titled “Beyond Ruby” at RubyConf Argentina in Buenos Aires.


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