Building Resilient AI Services Using Multi-Cluster Kubernetes

This webinar shows how to design and operate resilient multi-cluster Kubernetes platforms for AI workloads with Mirantis k0rdent AI. We’ll break down a practical reference pattern where training, inference, and shared services run in separate clusters so you can isolate GPU resources, reduce blast radius, and scale each layer independently. On top of that foundation, Mirantis k0rdent AI gives platform teams a consistent way to provision clusters, apply guardrails, and manage lifecycle operations across environments from a single control plane. You’ll see how Mirantis k0rdent AI helps standardize AI infrastructure with reusable templates for cluster builds and day-2 operations, while enforcing governance for multi-tenancy, quotas, and compliance. We’ll also show how Calico ClusterMesh and federated services enable secure, private east-west connectivity and consistent service discovery across clusters managed by k0rdent. Zero-trust micro-segmentation with Calico policies tightly controls cross-cluster traffic, and Calico observability makes it easier to validate flows and troubleshoot issues across clusters and namespaces. By the end, you’ll walk away with a clear blueprint for an AI-ready multi-cluster platform that’s more secure, more reliable, and easier to operate.