ai-cloud

GPU Cloud Platform with True Tenant Isolation

vCluster gives AI cloud providers fully isolated, CNCF-certified tenant clusters on bare metal GPU hardware, without provisioning separate physical clusters.

Trusted by the fastest-growing AI cloud providers
Problem

The GPU Cloud Platform Gap

GPU cloud providers face hard tradeoffs that slow revenue and erode margins.

Bare Metal Alone Falls Short

Selling raw compute is a race to the bottom. Customers want the cloud experience, not just GPU specs.

DIY Platform Takes Too Long

Building a GPU cloud platform in-house requires significant engineering investment, making it slow to stand up and costly to maintain.

Isolation vs. Efficiency Tradeoff

Namespace isolation is too weak. Separate physical clusters per tenant are too expensive to operate at scale.

Solution

One Stack from Bare Metal to Tenant Clusters

vCluster virtualizes the Kubernetes control plane, giving every tenant a real API server, etcd, and RBAC as a lightweight pod on shared GPU hardware. Boost Run launched a managed Kubernetes offering in under 45 days. Lintasarta launched in 90 days.

Built for GPU Cloud Providers at Scale

Every layer your GPU cloud platform needs, from bare metal provisioning to workload isolation, in one integrated stack.

Tenant Isolation

Isolated Tenant Clusters in Seconds

Each tenant gets their own API server, etcd, scheduler, and RBAC. For production workloads, Private Nodes, dedicated worker nodes with per-tenant CNI and storage, are the default. Shared Nodes serve dev, test, and trusted-team use cases. Spin up hundreds of isolated tenant environments with near-zero overhead.

  • Own API server per tenant
  • Spins up in seconds
  • No separate physical clusters needed
Bare Metal

Zero-Touch GPU Server Provisioning

PXE boot, OS installation, machine registration, and Netris-powered network automation handled automatically. Go from GPU rack to production Kubernetes without manual intervention or intermediate dependencies.

  • PXE boot to production automatically
  • Full GPU server lifecycle management
  • Ships with vCluster Standalone, no k3s or kubeadm required as a base layer
Workload Security

Kernel-Native Isolation Without VM Overhead

vNode delivers container breakout protection using seccomp, cgroups, namespaces, and AppArmor, preserving bare metal GPU performance. No hypervisor tax, no performance compromise on your GPU cloud.

  • No hypervisor overhead
  • Container breakout prevention
  • Full bare metal GPU performance
AI Environments

Production AI Platforms in Minutes

Partner integrations with Run:AI, Ray, and Jupyter turn a bare Kubernetes cluster into a production AI platform fast. Validated to run inside isolated tenant clusters without custom configuration.

  • Run:AI, Ray, Jupyter partner integrations
  • Cluster to AI platform in minutes
  • Tested with tenant isolation
Customer Experience

EKS-Like Portal for Your Customers

Give your GPU cloud customers a self-service portal to provision and manage their own environments. Deliver the managed Kubernetes experience AI teams expect without building a custom frontend.

  • Self-service environment provisioning
  • EKS and GKE-like experience
  • No custom portal engineering

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

What makes vCluster different from building a GPU cloud platform in-house?

Building a GPU cloud platform in-house requires significant engineering investment. vCluster delivers the full stack from bare metal provisioning to tenant cluster orchestration to workload isolation in one integrated platform. vCluster delivers the full stack from bare metal provisioning to tenant cluster orchestration to workload isolation in one integrated platform. Boost Run launched their managed Kubernetes offering in under 45 days.

How does vCluster provide tenant isolation on shared GPU hardware?

vCluster virtualizes the Kubernetes control plane itself. Each tenant gets their own API server, etcd, scheduler, and RBAC running as lightweight pods inside a control plane cluster on your shared bare metal GPU hardware. This gives every customer a fully isolated Kubernetes environment without the cost of provisioning separate physical clusters. For production deployments, Private Nodes deliver dedicated worker nodes with per-tenant CNI and storage, delivering hardware-level isolation. For dev, test, and trusted-team workloads, Shared Nodes provide namespace and resource-quota boundaries on shared infrastructure.

Is vCluster certified for production Kubernetes workloads?

Yes. Every tenant cluster created by vCluster is a CNCF-certified Kubernetes control plane with 100% API compatibility. Tenants get full cluster-admin access and can install their own CRDs, configure RBAC, and run any conformant Kubernetes workload. vCluster is named in the NVIDIA DGX SuperPOD reference architecture.

Can vCluster run directly on bare metal GPU servers?

Yes. vCluster Standalone runs as a single binary directly on Linux bare metal, no external Kubernetes dependency, no k3s, kubeadm, or k0s required as a base layer. The vMetal component adds zero-touch provisioning on top, handling PXE boot, OS installation, machine registration, and network automation from rack to production.

What GPU cloud providers are using vCluster in production?

vCluster powers over 100K GPU nodes across 50-plus GPU clouds and Fortune 500 customers, including CoreWeave and Nscale. Lintasarta launched in 90 days using vCluster. vCluster is named in the NVIDIA DGX SuperPOD reference architecture.

What isolation models does vCluster support for a GPU cloud platform?

vCluster offers a flexible isolation spectrum to match different customer tiers and security requirements. Private Nodes, the production default, give each tenant fully dedicated hardware with independent CNI and CSI. For dev, test, CI/CD, and trusted-team workloads, Shared Nodes provide namespace and resource quota boundaries. vNode prevents container breakout and limits blast radius at any tier without VM overhead, preserving near-bare-metal performance throughout.

Launch Your GPU Cloud Platform Faster

See how GPU cloud providers go from bare metal to managed Kubernetes in weeks.