DevOps Crime Scenes: Using AI-Driven Failure Diagnostics

Today, we have a special guest, Harpreet Singh, the co-founder and co-CEO of Launchable. Harpreet joins us to discuss an exciting frontier in software testing—using machine learning to predict failures and streamline the testing process.

Imagine a tool that can intelligently shift tests left in the development cycle, prioritize the most critical tests based on risk, and notify you via Slack when issues arise—all while continually learning and improving.

This is precisely what Harpreet and his team have achieved with Launchable. Their platform integrates seamlessly into CI/CD pipelines and provides engineering teams with valuable insights to speed up the process of identifying and fixing test failures.

In this episode, we'll delve into how Launchable aids in catching issues earlier, the profound influence of AI on the testing landscape, and real-life examples like BMW that illustrate the solution's effectiveness. We'll also explore Harpreet's advice on adopting a targeted approach to AI in DevOps and how their solution alleviates cognitive load, saving developers time and effort.

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