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A Jev-driven pipeline diagnosed 76.2% of 105 SRE faults

sregym.com 11 min read Editor score 7/10

A pipeline collects Kubernetes objects, events, pod logs and resource usage, then uses Jev to select likely causes; it passed 80 of 105 diagnoses with a 14.6-second median time. The measured result offers a concrete reference point for AI-assisted incident diagnosis without an LLM agent.

What

A Jev-driven pipeline diagnoses SREGym-Lite faults by programmatically collecting cluster evidence and using Jev to select likely causes.

How

The collector summarizes observations, Jev selects candidates and supporting evidence, and the pipeline assembles a report; it passed 80 of 105 diagnoses.

Why it matters

The pipeline’s evidence-collection and focused-decision stages offer a way to automate incident diagnosis without an LLM agent.

Read on sregym.com → Hacker News · 8 comments

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