Kubernetes Architecture Prover Connector for AI agents.

Yes, it forces resource limits on every container. It ensures that your workloads have defined memory ceilings so they won't crash the node.

Yes, it validates the manifest logic. It works regardless of whether you are on GKE, EKS, AKS, or a self-managed cluster.

It acts as a gatekeeper. It catches common AI hallucinations where the agent might skip security or reliability steps to keep the YAML simple.

Yes, it specifically looks for NetworkPolicies. It ensures you aren't running a flat network where every pod can talk to every other pod.

Yes, it is specifically designed for production-grade architecture. It focuses on the guardrails that prevent outages and security breaches.

The capability provides a specific verdict and coaching. It tells your agent exactly which part of the architecture is failing and how to fix it.

No. It validates that your architecture addresses the five production-critical pillars. resource governance, security hardening, reliability design, observability instrumentation, and network restriction. It does not generate YAML. It forces you to prove your YAML is production-ready.

Every container must have CPU and memory requests AND limits. Every namespace must have a LimitRange (defaults for containers that don't specify) and a ResourceQuota (ceiling for the namespace). 'The cluster handles it' is not governance. it is the absence of governance.

Yes. Managed Kubernetes handles the control plane. it does NOT handle your workload architecture. Resource limits, security context, PDBs, probes, and NetworkPolicies are YOUR responsibility on every provider. The cloud provider manages etcd. You manage everything that runs on the nodes.