What 400 million pipeline runs reveal about pipeline failures

We analyzed 400 million production pipeline runs, and what we found was surprising: code changes showed almost no correlation with failures at all.

For years, data teams have been told that adding CI/CD, writing tests, and tightening version control, the way software teams do, would make pipelines reliable. But, this is looking at the wrong layer entirely.

In this webinar, we’ll break down what the data actually showed, and where to redirect your effort to diagnose failures and keep pipelines reliable.

You’ll learn:

• Where pipeline failures actually come from, and why it isn't the code
• Why the deploy dashboard doesn't show you where failures actually start
• How data engineering already solved agentic AI's reliability problem