AIOps promises automated insights and remediation for Kubernetes, but most implementations fail due to implicit assumptions, brittle automation, and lack of standardization. This talk introduces a spec-driven approach to AIOps, where operational intent is explicitly defined, validated, and executed.

We demonstrate how Backstage can act as the central control plane for AIOps by treating specifications as the source of truth for observability signals, incident workflows, and remediation actions. Using real Kubernetes scenarios, we show how specs flow from Backstage into AI-assisted analysis and deterministic automation—ensuring predictable, auditable, and safe operations.

Attendees will learn how spec-driven AIOps reduces MTTR, avoids alert fatigue, and scales across teams without embedding fragile logic into pipelines. The session includes a reference architecture, design patterns, and practical takeaways platform teams can adopt immediately.