platform-eng

GPU Tenant Isolation Kubernetes Without VM Overhead

Stop trading GPU performance for security. vCluster virtualizes the Kubernetes control plane to deliver strong tenant isolation on shared GPU infrastructure without hypervisor overhead.

Trusted by the fastest-growing AI cloud providers
Problem

The GPU Isolation Tradeoff Is Real

Standard Kubernetes forces a painful choice between security and efficiency.

Namespace Isolation Is Too Weak

Tenants can see cluster-wide agents and other tenants' nodes. Namespace boundaries do not meet compliance requirements for shared GPU environments.

Separate Clusters Are Too Expensive

Provisioning physical clusters per tenant destroys GPU utilization and adds weeks of provisioning time for every new customer.

VMs Eliminate Your Performance Advantage

Hypervisor-based isolation introduces overhead that undermines the bare metal GPU performance your tenants are paying for.

Solution

Tenant Isolation at the Control Plane Level

vCluster virtualizes the Kubernetes control plane itself. Every tenant gets a real, CNCF-certified K8s cluster with its own API server, etcd, and RBAC, running as a lightweight pod on shared GPU infrastructure. For production deployments, Private Nodes deliver dedicated worker nodes with per-tenant CNI and storage, providing hardware-level isolation. Strong isolation, zero VM overhead, production-proven across 100K+ GPU nodes.

Full Stack GPU Tenant Isolation for Kubernetes

From control plane virtualization to kernel-native workload protection, vCluster delivers the complete GPU tenant isolation stack.

Control Plane

Isolated Tenant Clusters as Lightweight Pods

Each tenant gets a fully isolated Kubernetes control plane (own API server, etcd, and scheduler) running as a pod on the control plane cluster. Spins up in seconds with no physical cluster provisioning required.

  • Own API server per tenant
  • Seconds to provision tenant clusters
  • No separate physical clusters needed
Node Isolation

Dedicated Physical Nodes Per Tenant

Assign fully dedicated physical GPU nodes to a tenant with their own CNI and CSI. No workloads from other tenants ever share the hardware, significantly reducing cross-tenant blast radius.

  • Hardware-level tenant separation
  • Own CNI and CSI per tenant
  • No cross-tenant workload bleed
Workload Security

Kernel-Native Workload Isolation Per Tenant

vNode places every GPU workload in its own secure runtime using seccomp, cgroups, namespaces, and AppArmor. Prevents container breakout without any hypervisor tax on GPU performance.

  • No hypervisor, no performance tax
  • Significantly reduces container breakout risk, no hypervisor required
  • Works with gVisor and Kata Containers
Defense in Depth

Container Breakout Protection at Scale

Significantly reduce the risk of workload escape from container boundaries across every tenant cluster. Combines control plane isolation with kernel-native runtime security for a layered GPU tenant isolation Kubernetes architecture.

  • Layered control plane and runtime security
  • Reduces risk of cross-tenant escape
  • Layered tenant isolation across node and runtime
Compatibility

CNCF-Certified Kubernetes Per Tenant

Each isolated tenant environment is a fully conformant, CNCF-certified Kubernetes cluster. Tenants get 100% K8s API compatibility, not a proprietary subset, so their workloads run without modification.

  • 100% Kubernetes API compatibility
  • CNCF-certified per tenant cluster
  • No proprietary K8s surprises

Why vCluster

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.

100K+
GPU Nodes Powered
50+
GPU Clouds & F500s
<45
Days to Launch
30K
GitHub Stars

Get Started in 3 Steps

1
Schedule a Demo

Talk to our team about your stack

2
Deploy vCluster

Deploy vCluster on your infra in minutes

3
Onboard Your Tenants

Go live with a hyperscaler-grade tenant experience in days

FAQs

How does vCluster provide GPU tenant isolation in Kubernetes?

vCluster virtualizes the Kubernetes control plane itself. Each tenant receives a dedicated API server, etcd instance, scheduler, and RBAC scope running as a lightweight pod inside the control plane cluster. This gives every tenant complete control plane isolation without provisioning separate physical clusters or introducing hypervisor overhead. For production deployments, Private Nodes are the default: dedicated GPU worker nodes joined directly and privately into each tenant cluster with per-tenant CNI and storage, combined with vNode kernel-native runtime isolation for a full-stack GPU tenant isolation Kubernetes architecture.

Is this stronger than namespace-based Kubernetes isolation for GPU workloads?

Yes. Namespace isolation shares a single API server, etcd, and control plane across all tenants, meaning one misconfigured tenant can observe or affect others. vCluster gives each tenant their own isolated control plane. Tenants cannot see other tenants' nodes, pods, or cluster internals. For GPU environments where workloads are often untrusted or from competing teams, this distinction is critical.

Does tenant isolation in Kubernetes require VMs?

Not with vCluster. VM-based isolation introduces hypervisor overhead that degrades GPU performance, often unacceptable for AI training and inference workloads. vCluster delivers strong tenant isolation at the control plane level using lightweight pods, not VMs. For workloads requiring deeper isolation, vNode adds kernel-native security using seccomp, cgroups, and AppArmor without any hypervisor tax.

How many tenant clusters can run on shared GPU infrastructure?

vCluster has powered over 100K GPU nodes and runs millions of production clusters. Because tenant control planes run as lightweight pods rather than full physical clusters, the marginal cost per additional tenant is near zero. GPU clouds including Boost Run launched managed Kubernetes in under 45 days, and a GPU cloud in Indonesia launched in 90 days.

Can tenants install their own CRDs and operators inside isolated clusters?

Yes. Every tenant receives full cluster-admin privileges within their own tenant Kubernetes environment. They can install CRDs, configure RBAC, and deploy operators without any impact on other tenants or the control plane cluster. CRD and resource syncing between the tenant cluster and control plane cluster is also supported for workloads that require it.

Is vCluster used in production GPU cloud environments?

Yes. vCluster powers over 100K GPU nodes in production across 50 or more GPU clouds and Fortune 500 customers, including CoreWeave and Nscale. vCluster is named in the NVIDIA DGX SuperPOD reference architecture.

Ready to Isolate GPU Tenants Without Overhead?

See how vCluster delivers production-grade GPU tenant isolation, with Private Nodes as the production default for dedicated hardware isolation, and control-plane virtualization for every tenant.