I don’t currently work on a project that uses boost in production: my interest stemmed from adding support to Pulse for Boost.Test reports. However, the problem of large dependencies is a pretty common one. Opinions differ on the best way to handle such things.

Some people prefer to have their project as self-contained as possible, in which case they would check a dependency like boost in with their code. The obvious downside is clean checkouts become slow – so for continuous builds people often use incremental updates.

At the other end of the spectrum, you could require boost to be installed on any machine that runs the build. This keeps your codebase small, but has the disadvantage of needing to keep all the boost versions in sync (and risking using the wrong version by accident sometimes).

Somewhere in between the two, you could consider a dependency management tool. These are prevalent in the Java world, but not so much for C++. In our case we use Ivy. We store versioned binary dependencies in a repository (just files on a web server) and our projects declare what dependencies they need. The first time a project is built on a machine, Ivy pulls down the dependencies and caches them. Subsequent builds are fast as their dependencies are already in a local cache.