ruby

As mentioned in part 1 and part 2 of this series on Ruby's EventMachine, Thin is where most folks encounter EventMachine for the first time, even if they do not realize it. EventMachine is at the core of Thin and allows for the high concurrency that Thin provides to your Rails application. In this post I will look at Thin's usage of EventMachine.

In this post I am going to demonstrate, step-by-step, a way to A/B test new features from within Ruby-On-Rails using FluidFeatures. FluidFeatures is currently in closed-beta and requires request for inclusion in the beta program. We are looking for enthusiastic A/B testers, so we can get feedback on the service before releasing it to the masses.

In this post I will look synchronous vs asynchronous programming with Ruby's EventMachine, to show that asynchronous does not always mean that your code will run faster. In part 1 of this series on Ruby's EventMachine I discussed the benefits of event-based programming in general. I am a big fan of event-based programming, as you will see in these posts, but I wanted to flip the coin over and look at one of the down-sides of event-based programming.

In this first post, of a series on Ruby's EventMachine, I will introduce EventMachine and explain why event-based programming is good for your wallet. EventMachine, which just turned 1.0.0 this week, is more than just a gem, it is a new paradigm for many Ruby programmers and is not always easy to just drop into your existing stack. As the name suggests, it gives you event-based programming.

In this blog post I am going to introduce a new service for Ruby On Rails developers called FluidFeatures that helps you manage rolling out new features to your site and provides a way to easily do A/B testing (competing versions of a feature) right in the belly of your code.

Recently, we hit a problem with Ruby's exit command. If something went horribly wrong and it made no sense for our application to continue in its current state then we would abort with exit 1. We use supervisord to manage processes, so in this case when we exited with exit status of 1, supervisord would assume something went wrong and restart the process for us. Or at least that is what we thought...

In this blog post I will demonstrate a quick and easy way I have found to syntax highlight your Ruby code in pretty colors for your blog posts or other HTML-based display purposes. Please note, this blog post is designed for use with color monitors only, obviously. The focus of this post is Ruby, but this method also applies for syntax highlighting C, C++, Python, CSS, Clojure, diff, Groovy, HAML, ERB, Java, JavaScript, PHP, SQL, XML and YAML.

In this blog post I'll go through an example, in repeatable steps, of how to get up and running with the Tornado chat demo on ActiveState's public sandbox for Stackato. ActiveState's Stackato PaaS (Platform-as-a-Service) is based on VMware's open-source PaaS, Cloud Foundry, and offers an enterprise PaaS solution that will run on any public cloud, private cloud, laptop or desktop.

Geohashing is a simple way to encode latitude and longitude and grouping nearby points on the globe with varying resolutions. It was created by Gustavo Niemeyer. This blog post looks at how it's implemented any why it is such an elegant solution for encoding and managing location-based data.

Last week I attended a presentation by James Golick, CTO of fetlife.com. Intriguingly advertised as Scaling a Website to 300 Million Page Views Per Month with

In a few of my recent posts I have covered the ease of deploying clusters of Hadoop and Cassandra using Whirr. With Whirr you can simply write a

In this post I will explain the concept behind zero-copy, which is feature of the Linux allowing for faster transfer of data between pipes, file-descriptors and sockets. I will demonstrate how you can use this functionality in your Ruby projects using a code example. This functionality has been implemented in C, Java, Ruby, Perl and nameless other languages, but in this blog I will focus on the Ruby usage.

Here I demonstrate, with repeatable steps, how to fire-up a Hadoop cluster on Amazon EC2, load data onto the HDFS (Hadoop Distributed File-System), write map-reduce scripts in Ruby and use them to run a map-reduce job on your Hadoop cluster. You will not need to ssh into the cluster, as all tasks are run from your local machine. Below I am using my MacBook Pro as my local machine, but the steps I have provided should be reproducible on other platforms running bash and Java.

This is demonstration of installing Homebrew, the new Mac OS X package installer. Step-by-step instructions on installing Homebrew and using the brew command.

I'm getting stuck into learning Ruby On Rails and the topic of which tools / frameworks to use for testing came up. Here's some notes. I'll be reading up on