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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