A robust distributed locking algorithm based on Google Cloud Storage

Many workloads nowadays involve many systems that operate concurrently. This ranges from microservice fleets to workflow orchestration to CI/CD pipelines. Sometimes it's important to coordinate these systems so that concurrent operations don't step on each other. One way to do that is by using distributed locks that work across multiple systems.

Distributed locks used to require complex algorithms or complex-to-operate infrastructure, making them expensive both in terms of costs as well as in upkeep. With the emergence of fully managed and serverless cloud systems, this reality has changed.

In this post I'll look into a distributed locking algorithm based on Google Cloud. I'll discuss several existing implementations and suggest algorithmic improvements in terms of performance and robustness.

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A better way to reason about software testing terms

I was recently in a discussion between developers about improving the test coverage of a major software project. They needed guidance about what kind of tests to write, and how to write them.

The discussion quickly became confusing: the topic was too large, too general, and it turns out that there wasn't even a well-defined shared vocabulary for testing concepts! The latter turns out to be a wider problem in the software development community: it simply doesn't have well-defined testing terms!

In this post, I'd like to provide some guidance w.r.t. this matter. I'll discuss:

  • An overview of the most common testing terms.
  • A new way of reasoning about testing concepts: reiterating what actually matters, and categorizing tests based on "size" and "approach".
  • How the existing testing terminology fits in this new model.

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