From Policy Engine to AI-Native Platform: Introducing Cloud Agents for Infrastructure Governance

A journey in three acts What Cloud Agents do Under the hood: deterministic workflows, not freestyle agents A real example: Cost Analyzer in action Scheduling and operational integration The platform beneath the agents What comes next PRODUCT LAUNCH When we launched Nirmata, the goal was straightforward: give teams a better way to govern Kubernetes at scale. Kyverno has become the CNCF standard for Kubernetes policy enforcement. Nirmata Control Hub has become the enterprise control plane layered on top. And for the last few years, that has been the story — policy-as-code, applied at the cluster level, governed centrally. Then something changed. AI started showing up not just in the applications engineers were deploying, but in the tools they used to build and operate infrastructure itself. And we started asking a harder question: what does infrastructure governance actually look like in an AI-native world? Today, we’re sharing our answer: Cloud Agents — a new capability in Nirmata Control Hub that brings deterministic, AI-powered infrastructure analysis directly to your clusters, with a single click. We’ve been thinking carefully about AI agents — not just as a category of software, but as a spectrum of trust and autonomy. In a recent post , we laid out a practical taxonomy: Personal Agents Chat assistants on your device, acting on your behalf. High autonomy, creative, human in the loop (HITL). Service Agents Production workers with their own identity. Low autonomy, constrained, reliable.