AGNTCon + MCPCon Japan 2026

Kubernetes upgrades are high-stakes, deprecation-laden, and still mostly manual — most "AI for K8s upgrades" projects stop at a feasibility check. We went further: we built an agentic system that planned and executed a real cluster upgrade end to end, and in this talk we walk through exactly how it went, with the steps, evidence, and screenshots from our actual runs.

We'll break down the architecture we shipped — a planner → executor → verifier loop, deprecated-API and CRD/Helm compatibility analysis run before anything touched the cluster, a human-in-the-loop approval gate for irreversible steps, and health-gated automatic rollback. Using captured logs and screenshots, we'll show a real multi-node upgrade as it happened, the failure cases that nearly broke it (version skew, stuck drains, webhook deadlocks), and the decisions we deliberately refused to let the model make.

You leave with an open-source blueprint for autonomous infra agents with production-grade guardrails — plus real numbers on success rate, time saved, preflight catches, and rollbacks triggered.