Moving Beyond Kyverno to AI Platform Engineering

Moving Beyond Kyverno to AI Platform Engineering Kyverno OSS – Excellent Starting Point But Not The End Game Nirmata Enterprise for Kyverno – Kyverno Made Enterprise-Ready Centralized, Scalable Governance Enterprise-Grade Reliability Professional Support & Policy Best Practices AI-Powered Platform Engineering Assistance Remediator AI Agent: From Alert to Fix Command Line AI: Your Policy-as-Code Copilot When Does AI Platform Engineering Make Sense Over Kyverno A Practical Example Self-Service Control – AI as the Enabler, Not the Gatekeeper Trusting AI in the Platform: Reliability, Safety & Control AI That Supports Platform Engineers The Real Business Impact Improve Developer Velocity Strengthen Security and Compliance Scale Without Adding Headcount Reduce Operational Risk Bottom Line As platform engineers, most of us have been there: wrestling with hundreds of Kubernetes clusters, trying to enforce consistent security, compliance, and operational policies, all while balancing developer velocity and team efficiency. If you’ve relied on open-source Kyverno, you already know how powerful policy-as-code can be for Kubernetes governance. You’ve probably enjoyed Kyverno’s native integration with Kubernetes, its YAML-first approach, and the fact that it empowers teams to codify guardrails directly in your clusters. But as your infrastructure and engineering organization scale, the operational realities start to shift. What was sustainable for a handful of clusters becomes brittle and time-consuming at fleet scale. That’s where Nirmata’s AI-powered policy-as-code platform – including tools like the Remediator AI Agent , AI Copilot , and Command Line AI Platform Engineering Assistant come in. At its heart, this isn’t about replacing Kyverno; it’s about turning Kyverno into a scalable governance engine you can trust across your enterprise. Open-source Kyverno is a fantastic foundation for Kubernetes policy as code. It lets you enforce security guards, compliance standards, and operational best practices right in the Kubernetes control plane. You can write policies that validate, mutate, generate, and even cleanup resources in real time, all in native Kubernetes YAML. Its tight integration with GitOps workflows means that your policy definitions live where your code does, in version control, creating transparency and auditability. For early clusters and small teams, that’s often enough.