AI Cloud Provider Platform for Secure Tenant Clusters
vCluster gives AI cloud providers fully isolated, CNCF-certified tenant clusters on shared GPU infrastructure with near-zero overhead and no physical cluster sprawl.
vCluster gives AI cloud providers fully isolated, CNCF-certified tenant clusters on shared GPU infrastructure with near-zero overhead and no physical cluster sprawl.
Selling raw GPU compute is not enough. Your customers expect more.
Selling bare metal GPUs alone is a race to the bottom. Converging GPU specs mean margins erode unless you offer managed Kubernetes.
Namespace isolation is too weak. Separate physical clusters are too expensive. Standard Kubernetes forces you to choose.
Building a GPU cloud platform in-house requires significant engineering investment.
vCluster delivers the complete path from GPU racks to managed Kubernetes. Every tenant gets a fully isolated, CNCF-certified cluster with their own API server, etcd, and RBAC, running as a lightweight process on shared hardware. For production deployments, Private Nodes, dedicated worker nodes with per-tenant CNI and storage, deliver hardware-level isolation. Boost Run launched in under 45 days. Lintasarta in 90 days.
From bare metal provisioning to kernel-native workload isolation, vCluster covers every layer your AI cloud platform requires.
Each tenant gets a real Kubernetes API server, etcd, and scheduler running as a lightweight pod on your control plane cluster. Spin up hundreds of tenant environments without provisioning separate physical clusters.

vMetal handles PXE boot, OS installation, machine registration, and network automation across your GPU fleet. Go from rack to production-ready Kubernetes nodes without manual intervention.

vNode delivers container breakout protection using seccomp, cgroups, namespaces, and AppArmor per workload, preserving bare metal GPU performance with no hypervisor tax.

Turn a bare Kubernetes cluster into a production AI platform in minutes. Partner integrations with Run:AI, Ray, and Jupyter let you offer managed AI tooling to tenants without custom configuration work.

Give tenants an AWS-grade self-service experience. Your customers provision their own Kubernetes environments through a portal, without filing support tickets or waiting on your platform team.

This isn’t a side project. Behind every vCluster deployment is 5+ years of deep K8s engineering, security hardening, and battle-tested infrastructure work at massive scale.
Talk to our team about your stack
Deploy vCluster on your infra in minutes
Go live with a hyperscaler-grade tenant experience in days
Namespace isolation gives each tenant a partition of the same Kubernetes control plane, meaning they share the API server, etcd, and cluster-wide resources. vCluster gives every tenant their own dedicated API server, etcd, scheduler, and RBAC, running as a lightweight process on your control plane cluster. This means a tenant misconfiguration or compromise cannot affect other tenants, and each tenant gets full cluster-admin access without risk to the shared layer.
Boost Run launched its managed Kubernetes service in under 45 days using vCluster. Lintasarta launched a GPU cloud in Indonesia in 90 days, running hundreds of tenant clusters. The full stack, from bare metal provisioning through tenant cluster orchestration, is designed to get AI cloud providers to revenue without a lengthy multi-quarter build.
Yes. vCluster Standalone runs as a single binary directly on Linux, with no dependency on k3s, kubeadm, or any external Kubernetes distribution. vMetal handles PXE boot, OS installation, and network automation for your GPU servers, so the entire path from physical rack to tenant-ready Kubernetes clusters is covered in one integrated stack.
vCluster offers a flexible isolation spectrum. Private Nodes are the production default, giving a tenant fully dedicated physical nodes with their own CNI and CSI. Shared Nodes allow multiple tenants on the same physical hardware with resource quota boundaries, scoped to dev, test, CI/CD, and trusted-team workloads. At the workload layer, vNode prevents container breakout and limits blast radius using seccomp, cgroups, namespaces, and AppArmor, preserving near-bare-metal performance without hypervisor overhead.
Yes. vCluster powers over 100,000 GPU nodes in production across more than 50 GPU clouds and Fortune 500 customers, including CoreWeave and Nscale. vCluster is named in the NVIDIA DGX SuperPOD reference architecture.
vCluster supports air-gapped and FIPS deployments for environments with strict compliance requirements. Tenant control planes can run as VMs rather than pods to achieve OS-level kernel separation. vNode prevents container breakout and limits blast radius with seccomp, AppArmor, and cgroup enforcement. Network isolation is enforced via hardware-level VLANs, VXLANs, VRFs, and ACLs through the Netris integration, giving each tenant a fully segmented network boundary.
See how AI cloud providers go from GPU racks to tenant-ready Kubernetes in weeks.