BUILT FOR AI FACTORIES

Run AI On-Prem Where Your Data Lives

Power your AI factory with vCluster and vNode. Deliver secure, high-performance, multi-tenant Kubernetes for pre-training, fine-tuning, and inference workloads, right where your data lives.

You’ve Got the Hardware. Now Deliver the AI Experience.

Modern AI infrastructure demands more than GPUs; it needs a cloud-native control plane, workload isolation, and lifecycle automation. vCluster and vNode bridge the gap between traditional HPC hardware and the modern AI application layer.

  • Build scalable, multi-tenant environments for model training and serving

  • Avoid hypervisor overhead and VM sprawl

  • Provide cloud-like flexibility on bare metal or virtualized infra

The Platform Stack for On-Prem AI Factories

vCluster and vNode are the missing layer for bringing cloud-native AI infrastructure to on-prem environments. Deliver a secure, scalable, production-grade Kubernetes experience on GPUs—without rebuilding your platform stack.

Virtual Clusters

Provision isolated Kubernetes control planes for each AI team or workload.

  • Lightweight, production-ready Kubernetes
  • Full tenant-level RBAC, quotas, and policies
  • Compatible with MIG, MPS, DRA, and GPU schedulers

Virtual Nodes

Run isolated workloads on shared or dedicated GPU nodes; no hypervisors required.

  • Kernel-level security with native GPU access
  • High utilization and bare metal performance
  • Support for pre-training, fine-tuning, and inference

The Ideal Balance of Utilization and Control

Too often, AI infrastructure forces a tradeoff: maximize hardware use or ensure workload isolation—not both. vCluster and vNode eliminate that compromise, delivering secure, multi-tenant AI infrastructure with cloud-like flexibility and bare-metal performance.

Utilization
Isolation
Namespaces Only
Namespaces + MIG/MPS/DRA
vCluster + vNode
vCluster + vNode + MIG/MPS/DRA

Future-Proof Your AI Infrastructure with Flexible Tenancy Modes

Whether your use case is experimentation, production inference, or enterprise-scale training, vCluster supports all three GPU tenancy models, as well as hybrid setups.

  • 1. Shared Nodes
    Tenants share nodes dynamically within a single cluster, with isolation enforced at the node level using vNode. Ideal for batch inference or bursty AI workloads where high density matters. Shared services like CNI and CSI remain in place and require policies for secure multi-tenancy.
  • 2. Dedicated Nodes
    Each tenant is assigned dedicated GPU nodes using Kubernetes Node Selector, making it easy to isolate training or tuning workloads while still allowing flexible reassignment. Shared services such as CNI and CSI require additional policy controls for full isolation.
  • 3. Private Nodes
    Tenants get a fully isolated virtual cluster backed by private GPU nodes—effectively forming their own separate cluster. Ideal for sensitive or long-running model training. This includes isolated control planes, networking (CNI), storage (CSI), and all node-level components, delivering complete workload and infrastructure separation.

Runs on VMs or Bare Metal — Your Choice

vCluster is a certified Kubernetes distribution that runs on any standard Kubernetes node—virtualized or bare metal.

  • Works with vSphere, KVM, and bare metal GPU clusters
  • Provision Private Nodes using KubeVirt, ClusterAPI, OpenStack, or other open-source tools
  • Flexible enough to support hybrid infrastructure setups

Trusted by Hardware & Platform Leaders

“We needed a way to deliver cloud-like AI infrastructure in private data centers. vCluster gave us a Kubernetes-native path to scale across hundreds of nodes with full isolation and lifecycle control.”

AI Infrastructure Architect, Global Hardware Vendor

vCluster: Deliver Isolated Kubernetes for Every AI Team

Create lightweight, production-grade virtual clusters across your private AI infrastructure.

vNode: Run Secure, High-Performance GPU Workloads at Scale

Securely isolate GPU workloads for model training, tuning, and inference, without VM overhead.

  • Hardened Isolation: Enforce kernel-level security on shared or dedicated GPU nodes

  • Bare Metal Speed: Direct GPU access with zero hypervisor tax

  • Flexible Tenancy: Support dedicated, shared, and hybrid models on one platform

  • AI/ML-Optimized: Built for performance-sensitive LLMs, fine-tuning, and real-time inference

  • Day-2 Ready: Scales to hundreds of nodes with simplified operations and updates

Why Enterprise Platform Teams Choose vCluster + vNode

Boost GPU ROI
Maximize utilization across
AI factories

Ensure Strong Isolation
Support secure multi-tenancy and compliance

Accelerate Provisioning
Launch environments in seconds,
not hours

Infrastructure Agnostic
Works on any certified
K8s distro

Simplify Day-2 Ops
Handle upgrades, operators, and config at scale

Flexible Tenancy
Shared, dedicated, or hybrid—all supported natively

Ready to Power the Next Generation of On-Prem AI?

Let’s talk about how vCluster helps deliver Kubernetes-native AI infrastructure across your private GPU fleet.