Automated Root Cause Analysis: The Complete Guide
Automated root cause analysis, end to end: how to automate the hours of investigation before the fix, on the telemetry tools you already run. Get the guide.
The fix for most incidents takes minutes: a rollback, a config change. The hours go to finding out what to change. Automated root cause analysis hands that search to software, and gives your engineer a causal chain to check with the evidence attached.
Published results show how wide the spread is. Microsoft reports 76.6% accuracy from a system grounded in past incidents. On an open benchmark, the best model working from raw telemetry solved 11% of cases. Both used frontier models. The guide shows what made the difference, and how to build for it.
It is written for the people who will build it: working configuration and code on open-source tools, a worked incident from alert to approved rollback, and nothing you need to buy to follow along.
Inside the guide
The eight techniques behind automated RCA, from rules to AI agents, compared in one table.
A nine-step build on OpenTelemetry, Prometheus, Loki and Tempo, with configuration and code.
How to put an AI agent on top: tool design, Context Engineering, and six rules that stop a confident wrong answer.
A worked incident, from the alert to an approved rollback, with every piece of evidence shown.
How to measure it: a replay suite of past incidents, and the metrics that move before MTTR does.
Twelve failure modes, what each looks like in production, and the fix.
A five-level maturity model and a 90-day plan.
Where NeuBird fits alongside the observability tools you already run.
Related Resources
See NeuBird in action
Root cause in minutes, not war rooms.