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GitLab had 38 public incidents in Q1 2026, up 36% from Q1 2025. March alone had 20, almost one per working day. They even have an active incident as I write this on April 1st, and, sadly, this isn't even an April Fool's joke.

Looking at their status page history, there is a consistent pattern: a code change gets deployed, breaks production, the team identifies the bad MR, and has to revert it. CI/CD pipelines are the most frequently affected component, and the incidents are noticeably impacting our development workflow.

I get it, these things happen to us too. Having to revert bad code changes every now and then is part of working on a complex real-world production system. But what makes this difficult to accept isn't just the trend itself. GitHub's status page is arguably even worse, but at least GitHub appears to be consistently ahead on AI features. GitLab appears to be getting the worst of both worlds: increasing instability without access to the latest capabilities, such as the Claude Code integration. If you're going to break things, you should at least be shipping something valuable and exciting regularly.

I think there's a real question here about whether the industry has crossed a threshold where the speed of shipping with AI tools has outpaced existing deployment systems' ability to catch problems before they reach production. The irony is that GitLab's product is literally about helping teams ship code safely. If the company that builds the CI/CD platform is struggling with this, it might be an early signal that everyone needs to rethink how deployment safety scales when AI dramatically increases the pace of change.

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