Ken Muse

A few weeks ago I went in for some simple tests as we tried to uncover the root cause of a sudden heartburn. With each test I took, we discovered that my condition was substantially worse than it seemed. I was running out of time quickly, and the doctors had to act fast.

Most package management systems support some kind of "universal artifacts" storage. Azure Artifacts supports "universal packages", Artifactory supports "generic repositories", and Nexus has "raw repositories". But what about GitHub? From all appearances, it would seem this is an oversight. Although not explicitly documented, it turns out it's fully supported.

If you've ever wanted to integrate an external system or execute parts of the CI process asynchronously, the GitHub Checks API can provide a way to make that happen. In fact, you can even use Checks to allow two workflows to work together, no waiting or polling from the runner required. Today I'll demonstrate how the API works and provide two workflows that demonstrate how to build a working GitHub Check.

Most people don't realize that the humble pull request orchestrates surprisingly complex activities behind the scene. GitHub creates test merges and simulated merge branches to test and validate what would happen if the changes were merged into the target branch. This is more complex than most people realize, and it leads to a number of different SHAs being provided to the GitHub workflow. It's time to understand these SHAs, their purpose, and how to find them.

Monorepos are often seen as the simple solution to complex collaboration and code management problems. Companies like Google and Facebook frequently mention their use of the pattern for their most important codebases, so clearly they have found ways to make these solutions scale to support large teams. What is their secret to being able to successfully use a monorepo, and how do they make it work where so many others fail? More importantly, should you be considering the approach?