It’s not really an exploration of PDBs and debugging without talking about symbol servers. With .NET evolving, has our need for these previously essential systems changed? In this post, we’ll explore what a symbol server is, the role they fill, and their strengths and limitations.

Years ago, John Robbins examined the details of PDB files in PDB Files: What Every Developer Must Know. Since then, a lot has changed about .NET. Despite that, most developers still lack an understanding of how PDBs work or why they are so important. Most times, I see teams trying to prevent PDBs from being created in release code; this is a sure path to future problems. In this post, I’ll provide updated details on the nature of PDBs and how they work.

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.