ai-cloud

GPU Cluster Isolation for AI Clouds

Private Nodes dedicate worker nodes to each tenant cluster. A separate virtualized control plane gives every tenant its own API server and RBAC boundary, while Netris can enforce network isolation in the physical fabric.

Trusted by the fastest-growing AI cloud providers
Problem

Why Generic Isolation Fails at Scale

GPU tenant isolation needs clear boundaries at the control plane, worker node, and network layers.

Namespace Isolation Is Too Weak

Namespace-only designs share control-plane and node-level components between tenants.

Separate Clusters Are Too Expensive

Running a separate management stack for every tenant increases infrastructure and operational work.

No Control Plane Boundaries

A shared API server and RBAC model cannot provide the same tenant control-plane boundary as a dedicated tenant cluster.

Solution

Full-Stack Tenant Isolation From Control Plane to Kernel

vCluster gives every tenant its own virtualized control plane and uses Private Nodes as the production default. Optional vNode and Netris integrations strengthen the runtime and physical network boundaries.

Full-Stack GPU Cluster Tenant Isolation

GPU cluster isolation spans the tenant control plane, dedicated Private Nodes, optional runtime isolation, and optional hardware network isolation.

Hardware Isolation

Private Nodes Per Tenant Cluster

Private Nodes assign dedicated worker nodes with tenant-scoped networking and storage to each production tenant cluster.

  • Per-tenant CNI and storage
  • No cross-tenant workload placement
  • Hardware-level security boundary
Control Plane

Virtualized Control Planes Per Tenant

Each tenant receives its own virtualized Kubernetes control plane, API server, and RBAC boundary.

  • Own API server and etcd per tenant
  • Lightweight control plane
  • Isolated blast radius per tenant
Workload Security

Kernel-Native Workload Isolation

vNode adds a tenant isolation runtime using Linux user namespaces and seccomp filters for workloads that need a stronger runtime boundary.

  • Container breakout protection
  • No hypervisor performance tax
  • Hardened to the kernel
Network Isolation

Hardware-Enforced Network Boundaries

Netris integration can place each tenant network environment on a separate hardware-backed L2 boundary.

  • VLANs and VRFs per tenant
  • Network automation
  • Hardware-enforced network boundaries
Compliance

Air-Gapped and FIPS Deployments

vCluster Platform supports air-gapped deployments and FIPS features on supported plans for regulated deployment patterns.

  • Air-gapped deployment support
  • FIPS features on supported plans
  • Sovereign and regulated environments

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+
GPUs 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

What makes vCluster's GPU cluster isolation stronger than Kubernetes namespaces?

Namespace-only designs share the Kubernetes control plane and node-level components. vCluster gives each tenant a separate virtualized control plane, while Private Nodes assign dedicated worker capacity to each production tenant cluster.

How does vCluster Platform handle GPU workload isolation between tenants?

vCluster covers control-plane and worker-node isolation. vNode can add a stronger runtime boundary using Linux user namespaces and seccomp filters. GPU presentation, including MIG or vGPU, remains the responsibility of the GPU operator, device plugin, and driver stack.

Can vCluster support compliance requirements for tenant isolation on GPU infrastructure?

vCluster Platform supports air-gapped deployments and FIPS features on supported plans. Private Nodes and optional Netris network isolation provide deployment controls for regulated environments without claiming compliance on the customer's behalf.

What cluster types can run as isolated tenant environments on vCluster Platform?

vCluster can power managed Kubernetes, Slurm, Ray, inference, and other tenant cluster products. Run:AI remains responsible for its scheduling capabilities, and Slurm remains responsible for Slurm scheduling.

How quickly can an AI cloud provider deploy tenant isolation on GPU infrastructure with vCluster?

vCluster provides turnkey tenant management and APIs for a custom experience. Templates, capacity policy, and centralized fleet operations reduce the platform work required to launch and operate tenant clusters.

Does vCluster's isolation model require provisioning separate physical clusters per tenant?

No separate Kubernetes control-plane servers are required for each tenant. The tenant control plane runs as isolated pods, while Private Nodes provide dedicated worker capacity for production workloads.

See GPU Cluster Isolation in Action

Learn how 50+ GPU clouds implement tenant isolation with vCluster.