Build failures in Kubernetes CI/CD pipelines are a silent productivity killer. Developers spend 45+ minutes scrolling through cryptic logs, often just hitting rerun and hoping for the best.

Ron Matsliah, DevOps engineer at Next Insurance, built an AI-powered assistant that cut build debugging time by 75% — not as a dashboard, but delivered directly in Slack where developers already work.

In this episode:

Why combining deterministic rules with AI produces better results than letting an LLM guess alone
How correlating Kubernetes events with build logs catches spot instance terminations that produce misleading errors
Why integrating into existing workflows and building feedback loops from day one drove adoption
The prompt engineering lessons learned from testing with real production data instead of synthetic examples

The takeaway: simple rules plus rich context consistently outperform complex AI queries on their own.

Sponsor

This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training.

More info

Find all the links and info for this episode here: https://ku.bz/PDdYfC00w
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How We Cut Build Debugging Time by 75% with AI, with Ron Matsliah

KubeFM

How We Cut Build Debugging Time by 75% with AI, with Ron Matsliah