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Human-in-the-loop runbook improvement with agentic support automation.

By Rocker D'Antonio, Harry Xie
2025
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Operational support is an important component of production software services. Support requests are often emergent and can come in many forms such as customer escalations or unplanned service interruption. Engineers across organizations have been successful in implementing automation to help streamline support processes but many solutions remain in the hands of human operators. A successful strategy to improve operator response times is to maintain up-to-date runbooks which are documents enumerating triage steps and remediation procedures in the face of identified incidents. This paper is an investigation into an operational system which incorporates Agentic AI into a runbook based incident resolution pattern. The bot uses information in the runbook corpus along with some system-specific tooling to guide the manual operator through the mitigation process then evaluate the outcome and suggest edits to the runbook where it found gaps and in its ability to triage the situation. By using the runbook as a medium to bridge humans and automation, the process maintains explainability and can be decoupled from the agent system. This paper demonstrates a collaboration between human operators and Agentic AI with results from an 17 week study involving 232 production incidents. We conclude with lessons on integrating LLMs into DevOps workflows, related work in AI-assisted operations, and guidance for reproducibility.
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