People keep asking us here at Checkly if and how AI can help create solid and maintainable Playwright tests. To answer all these questions, we started by looking at ChatGPT and Claude to conclude that AI tools have the potential to help with test generation but that "normal AI consumer tools" aren't code-focused enough. High-quality results require too complex prompts to be a maintainable solution.

We all implement tools to monitor our nodes and keep our entire cluster up and running. But how often do updates, failures, or errors mean that users suffer outages, even though our status boards look green? As Kubernetes has enabled more complex microservice architecture, the gap between the state of the dashboard, and the health of services for the user, has grown wider.