Agentic runbooks are AI-powered automation systems that continuously observe Kubernetes cluster state, make autonomous remediation decisions, and verify outcomes without human intervention. Unlike traditional automated runbooks that execute predefined scripts, agentic runbooks reason about context and handle multi-step recovery workflows end to end. Three key scenarios are covered: OOM event handling (auto-adjusting memory limits), Spot instance interruption recovery (provisioning replacements within the 30-second warning window), and node consolidation/bin-packing (continuous loop to reclaim idle compute). Effective agentic runbooks require observability, write-level actuation, and post-fix verification. Cast AI's Application Performance Automation (APA) platform implements these as closed-loop workflows, with customers reporting 40–70% cloud cost reductions and up to 80% fewer incidents requiring human intervention.
Table of contents
Three Levels of Runbook MaturityThree Kubernetes Agentic Runbook ScenariosWhat Agentic Runbooks Actually RequireCast AI’s APA Platform: An Agentic Runbook Engine for KubernetesHow to Get Started with Agentic Runbooks on KubernetesHow to Evaluate Whether Your Cluster Needs Agentic RunbooksThe Operational ShiftFrequently Asked QuestionsSort: