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
Based on industry experience, building a GPU cloud platform typically requires 6 to 10 engineers, 6 to 12 months, and over $1M in investment.
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 built a GPU cloud 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 on your GPU cloud platform gets their own API server, etcd, scheduler, and RBAC — running as a lightweight pod. Spin up hundreds of isolated tenant environments on shared bare metal 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 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
- No k3s or kubeadm required
Workload Security
Kernel-Native Isolation Without VM Overhead
vNode (currently in private beta) 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
Pre-validated environments for Run:AI, Ray, and Jupyter turn a bare Kubernetes cluster into a production AI platform fast. Certified to run inside isolated tenant clusters without custom configuration.
- Run:AI, Ray, Jupyter pre-validated
- 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?
Based on customer experience, building a GPU cloud platform in-house typically requires 6 to 10 engineers, 6 to 12 months, and over $1M in investment — and in our experience, most teams are still building two years later. 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 with zero new platform engineering hires.
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 host 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 stronger isolation, tenants can be placed on dedicated or private nodes.
Is vCluster certified for production Kubernetes workloads?
Yes. Every tenant cluster created by vCluster is a CNCF-certified Kubernetes distribution 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 also named in the NVIDIA DGX SuperPOD reference architecture and in the SemiAnalysis ClusterMax evaluation criteria.
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 Indonesia's leading GPU cloud in 90 days using vCluster and now runs 170-plus isolated tenant clusters in production. 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. Options range from shared nodes with namespace and resource quota boundaries, to dedicated nodes that eliminate noisy-neighbor GPU contention, to private nodes with fully dedicated hardware and independent CNI and CSI. vNode (currently in private beta) adds kernel-native workload isolation at any tier without VM overhead, preserving bare metal GPU performance throughout.
Launch Your GPU Cloud Platform Faster
See how GPU cloud providers go from bare metal to managed Kubernetes in weeks.
