Preface

In 2011, I started working at Amazon.com. In that first week my life was changed as I learned how to use their internal build, dependency modeling, and deployment tooling. This was the kind of automated management I had always known was possible but had never seen. I was coming from a team that would deploy quarterly and take 10 hours to do so. At Amazon I was watching rolling deployments push changes I had made earlier that day to hundreds of machines spread all over the globe. If big tech firms had an engineering advantage over the rest of the corporate landscape, this was it.

Early in 2013, I wanted to work with Graphite (a metrics collection and graphing suite). One day I sat down to install the software and start integrating a personal project. At this point I had several years of experience working with open source applications, but few were as dependent on such large swaths of the Python ecosystem. The installation instructions were long and murky. Over the next several hours, I discovered many undocumented installation steps. These were things that might have been more obvious to a person with deeper Python ecosystem knowledge. After pouring over several installation guides, reading through configuration files, and fighting an epic battle through the deepest parts of dependency hell, I threw in the towel.