AI Incident Response Agent

The problem

Production incidents often require engineers to manually correlate alerts, search multiple log sources, inspect metrics, review operational runbooks, and determine root causes under time pressure. This process is repetitive, time-consuming, and highly dependent on individual experience, increasing the Mean Time to Resolution (MTTR).

The solution

I designed a ReAct-based AI agent that dynamically chooses investigation tools according to the incident context. The agent retrieves relevant logs, metrics, and operational runbooks through Retrieval-Augmented Generation (RAG), reasons over the collected evidence, and produces structured incident reports with root cause analysis, confidence assessment, and recommended remediation steps.