KubeClipper vs vCluster Platform

KubeClipper is a free, open-source service for managing Kubernetes clusters on an organization’s own infrastructure. Its web interface, APIs, and kcctl command-line tool support cluster deployment and lifecycle operations across cloud, hypervisor, and bare-metal environments. Users can create, delete, upgrade, back up, restore, and scale clusters, and register clusters built elsewhere. Deployment can be online, offline, or through a proxy; a graphical wizard helps set up clusters and required plugins. Node tools include automatic registration, information collection, and a terminal. Access controls include role-based and custom permissions, with OIDC login for external users. Backups cover etcd data and Kubernetes resource objects, using filesystem or S3 storage such as NFS or MinIO; files produced by resources and files on persistent volumes are outside that backup scope. The project lists x86/64 and arm64 support and extensible management of CRI, CNI, CSI, and CRD components. Worker-node addition and removal are the currently supported node changes.

vCluster Platform is a management plane for deploying, configuring, and operating tenant cluster fleets through a web UI, CLI, and API. It manages tenants across EKS, GKE, AKS, bare metal, and private cloud, with isolated tenant clusters and shared-node, dedicated-node, private-node, Auto Nodes, and Standalone tenancy models. With vCluster Cloud, the platform is hosted while host and virtual clusters remain in the customer's infrastructure; self-hosted deployment puts the full platform there. The Free plan is free and permits unlimited virtual clusters within a limit of 64 CPUs or 32 GPUs, with a maximum of one HA vCluster. It also supports provisioning, multi-cluster management, policy enforcement, and upgrade management. Listed integrations include Terraform, Rancher, Argo CD, HashiCorp Vault, and Istio. Enterprise features include SSO, audit logging, vulnerability alerts, security review, FIPS-compliant images, enterprise support, and SLAs. One isolation caveat is that shared nodes share several underlying components across tenants, including the kernel, kubelet, node filesystem, and host network. The maker describes use by AI cloud providers and public and private cloud teams.