vCluster

vCluster provides virtualized Kubernetes control planes for multi-tenant environments. It offers a middle ground between namespace-level multi-tenancy, where tenants share cluster-wide APIs and custom resource definitions (CRDs), and provisioning completely independent clusters, which increases operational overhead. With vCluster, each tenant gets its own Kubernetes API server, controller manager, data store, RBAC and CRDs. The control plane runs as a lightweight workload on the underlying infrastructure, allowing standard tools such as kubectl, Helm and GitOps controllers to interact with each tenant independently.

We've successfully used vCluster to build managed Kubernetes services and AI cloud environments where balancing tenant isolation against operational costs is critical. It’s particularly attractive for AI platforms where different customers may need their own GPU operators, schedulers, inference frameworks and CRDs. For trusted workloads, virtualized control planes can share underlying compute resources. For customer-facing GPU environments, dedicated worker nodes can provide stronger workload isolation while retaining consolidated control plane management. Given its success in production client environments, we're placing vCluster in Trial.