Most systems drown in meaningless WARNING logs. They waste money, obscure real errors, and help no one. Here’s why your next logging cleanup should start by deleting WARNING — and how structured logs make your production systems clearer, cheaper, and safer.

Code reviews often fail not because the code is wrong, but because no one knows why it was written that way. This post explores how AI-generated comments can add missing intent to pull requests—making both human and AI reviews smarter, faster, and more effective.

Floating versions like :latest, ^, and ~ promise convenience but deliver broken builds, hidden regressions, and supply chain risks. Here we explain why they undermine reproducibility and security and shows how to pin GitHub Actions, Docker images, and dependencies safely.

Permissions drift is real: scattered checks, forgotten filters, and data leaks. PostgreSQL’s Row Level Security (RLS) flips the script: pushing verification into the database for stronger safety, but with trade-offs in debugging and performance.

From Bors and Homu to Bulldozer, Kodiak, Mergify, and now GitHub and GitLab, merge queues have shaped how we keep main branches green. This article traces their history, why they emerged, and how they became a standard in modern software development.

Building a Jenkins plugin sounded simple — until it became a crash course in Java, Jenkins internals, and community code review. Here’s what I learned, why the process surprised me, and how it now powers Mergify CI Insights.

Pull requests are essential, but they don’t scale without automation. Learn PR basics, best practices, and how to automate reviews, tests, and merges with GitHub Actions or Mergify.

Trunk-based vs Gitflow: which branching model really works for modern CI/CD? We compare both, share trade-offs, and argue why trunk-based (with automation like merge queues) usually wins for teams that care about speed, reliability, and flow.

A feature branch workflow is one of Git’s most popular strategies. Learn how it works, its pros and cons, and how modern automation (like merge queues) keeps feature branches fast, safe, and frustration-free.