ai-cloud
Your Hybrid Kubernetes GPU Cloud Control Plane
Unify on-premises and public cloud GPU infrastructure from a single control plane. vCluster delivers isolated tenant clusters at bare metal speed across your entire hybrid environment.
Trusted by the fastest-growing AI cloud providers
Problem
Hybrid GPU Infrastructure Is Hard
Managing GPU workloads across on-prem and cloud exposes three critical gaps.
Isolation Breaks at Scale
Namespace isolation is too weak for multi-tenant GPU workloads. Separate physical clusters are too expensive and slow to provision.
Siloed Control Planes
On-prem and cloud GPU resources operate in separate silos, making unified scheduling, billing, and tenant management nearly impossible.
VM Overhead Kills GPU Performance
Traditional hypervisor-based isolation taxes GPU throughput. Tenants pay for VMs but demand bare metal performance.
Solution
One Control Plane for Your Entire GPU Stack
vCluster virtualizes the Kubernetes control plane itself, running CNCF-certified tenant clusters as lightweight pods across both on-prem and cloud GPU nodes. Powered in production across 100K+ GPU nodes and 50+ GPU clouds, it unifies your hybrid Kubernetes GPU cloud without VM overhead.
Built for Hybrid Kubernetes GPU Infrastructure
Every layer of your hybrid GPU cloud covered — from bare metal provisioning and tenant isolation to multi-region orchestration and certified AI stacks.
Tenant Isolation
Isolated Tenant Clusters at Bare Metal Speed
Every tenant on your hybrid Kubernetes GPU cloud gets a dedicated API server, etcd, scheduler, and RBAC — running as a lightweight pod. No VM overhead. Spins up in seconds across on-prem and cloud nodes.
- Full K8s API server per tenant
- Seconds to provision, not hours
- No hypervisor tax on GPU throughput
Hybrid Orchestration
Unified Control Across Clouds and Data Centers
A single control plane spans your on-premises GPU racks and public cloud regions. Manage tenant cluster placement, resource quotas, and scheduling policies from one central interface across your entire hybrid footprint.
- Single pane across on-prem and cloud
- Central quota and policy management
- Consistent tenant experience everywhere
Bare Metal
Zero-Touch GPU Server Provisioning
vMetal handles PXE boot, OS installation, machine registration, and network configuration for every GPU server in your hybrid environment. Go from rack to production-ready Kubernetes node with no manual intervention.
- PXE boot to K8s node automatically
- Full GPU server lifecycle management
- Network automation via Netris integration
Workload Security
Kernel-Native Isolation Without VM Overhead
vNode (currently in private beta) secures each workload using seccomp, cgroups, namespaces, and AppArmor at the kernel level — preventing container breakouts without a hypervisor. Your hybrid Kubernetes GPU cloud delivers strong isolation at full bare metal GPU speed.
- Container breakout protection built in
- Zero hypervisor tax on GPU workloads
- Defense-in-depth with control plane isolation
AI Readiness
Production AI Environments in Minutes
Pre-validated AI stacks including Run:AI, Ray, and Jupyter turn a bare tenant cluster in your hybrid GPU cloud into a production AI platform in minutes — not weeks of integration work.
- Run:AI, Ray, Jupyter pre-validated
- Cluster to AI platform in minutes
- Tested against vCluster tenant isolation
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 suited for a hybrid Kubernetes GPU cloud?
vCluster virtualizes the Kubernetes control plane itself, running each tenant cluster as a lightweight pod rather than a separate physical cluster or namespace partition. This means you can span isolated tenant environments across both on-premises GPU racks and public cloud regions from a single control plane — without VM overhead degrading GPU throughput. It is production-proven across 100K+ GPU nodes and named in the NVIDIA DGX SuperPOD reference architecture.
How does vCluster handle tenant isolation across on-prem and cloud nodes?
Every tenant receives a dedicated API server, etcd, RBAC, and CRDs regardless of where their workloads run. vCluster supports a flexible isolation spectrum from shared nodes through private dedicated nodes. vNode (currently in private beta) adds kernel-native workload isolation using seccomp, cgroups, and AppArmor — preventing container breakouts at bare metal GPU performance levels. Network isolation is enforced via hardware-backed VLANs, VXLANs, and VRFs through Netris integration.
Do tenant clusters run in VMs or pods?
By default, tenant control planes run as lightweight pods inside the host cluster, delivering seconds-fast provisioning with no hypervisor overhead. For environments requiring OS-level separation, control planes can run inside dedicated VMs. Either way, workload nodes run directly on bare metal GPU hardware — preserving full GPU performance for tenant workloads.
Can vCluster provision bare metal GPU servers as part of the hybrid stack?
Yes. vMetal provides zero-touch bare metal provisioning — handling PXE boot, OS installation, machine registration, and network automation for GPU servers. vCluster Standalone then runs as a single binary directly on bare metal with no external Kubernetes dependency, eliminating the need for k3s or kubeadm as intermediate layers. This delivers a complete path from GPU rack to managed Kubernetes.
How quickly can a GPU cloud provider launch on vCluster?
Boost Run launched a managed Kubernetes offering in less than 45 days with zero new platform engineering hires. Lintasarta built Indonesia's leading GPU cloud in 90 days using vCluster, deploying 170+ tenant clusters. The platform is designed to compress the typical 6-to-12-month build timeline for teams that would otherwise construct a hybrid Kubernetes GPU cloud from scratch.
Is vCluster Kubernetes-conformant across hybrid environments?
Yes. Every tenant cluster provisioned by vCluster is CNCF-certified and 100% Kubernetes API-compatible. Tenants operating in a hybrid Kubernetes GPU cloud environment receive a fully conformant cluster — not a proprietary or partial implementation — regardless of whether their workloads run on on-premises GPU servers or public cloud nodes. This ensures existing Kubernetes tooling, operators, and workflows work without modification.
Launch Your Hybrid GPU Cloud Today
See how vCluster unifies on-prem and cloud GPU infrastructure for your tenants.
