Containerisation technology is becoming more and more popular because it provides an efficient way to improve deployment flexibility by packaging up code into software micro-environments. Yet, containerisation has limitations and one of the main ones is the fact that entire container images need to be transferred before they can be used. Container images can be seen as software stacks and High-Energy Physics has long solved the distribution problem for large software stacks with CernVM-FS. CernVM-FS provides a global, shared software area, where clients only load the small subset of binaries that are accessed for any given compute job.
In this paper, we propose a solution to the problem of efficient image distribution using CernVM-FS for storage and transport of container images. We chose to implement our solution for the Docker platform, due to its popularity and widespread use. To minimise the impact on existing workflows, our implementation comes as a Docker plugin, meaning that users will continue to pull, run, modify, and store Docker images using standard Docker tools.
We introduced the concept of a “thin” image, whose contents are served on demand from CernVM-FS repositories. Such behavior closely reassembles the lazy evaluation strategy in programming language theory. Our measurements confirm that the time before a task starts executing only depends on the size of the files actually used, minimizing the cold start-up time in all cases.