Aggregate distributed GPU capacity across public cloud, AI clouds, and bare metal into one Kubernetes control plane.
You need a unified operations layer, not a different Kubernetes stack for every supplier.
Every new compute source ships with its own Kubernetes flavor, networking model, and upgrade cycle. Your team rebuilds the integration from scratch every time.
Your infra team is managing EKS, GKE, k3s, and bare metal simultaneously. Nothing is shared. Expertise doesn’t transfer. On-call gets worse every quarter.
Onboarding a new GPU supplier takes months. There’s no shared playbook, only bespoke runbooks per source and no failover when a supplier goes down.
vCluster normalizes your entire fleet under one operational model. Same playbook. Every supplier. Every time.
One ops team managing your entire compute fleet. Every GPU supplier onboarded through the same repeatable playbook. Zero per-provider tooling, custom integrations, or fragmented runbooks.
vCluster delivers the complete infrastructure stack for teams building distributed inference platforms, from bare metal provisioning through tenant-isolated GPU environments and inference gateway integration. Each layer is production-proven and works independently or as a unified platform.
Strong isolation, zero VM overhead
Each workload runs in its own secure runtime using kernel-level isolation, seccomp, cgroups, namespaces, and AppArmor. No VMs, no hypervisor tax.
Bare metal GPU performance with strict boundaries
Direct GPU access with near-zero overhead. Full performance for your tenants with strict security boundaries between every workload.
Purpose-built for untrusted customer inference workloads
Designed for dynamic code execution, package installs, and root access, safely. Built for inference platforms running customer workloads on shared GPU infrastructure.
Every customer gets their own Kubernetes environment
Give each tenant a fully isolated control plane, their own API server, etcd, and RBAC, on shared GPU infrastructure. No separate physical clusters required.
Maximize GPU utilization across shared infrastructure
Run hundreds of isolated tenant clusters on a single host cluster. Isolate tenants while maximizing utilization of every GPU in your fleet.
Platform-level control at scale
Manage clusters, policies, and lifecycle across your entire platform from one control plane. Provision via CI/CD, APIs, or self-service portals in seconds.
Zero-touch bare metal provisioning
PXE boot and configure GPU servers automatically. New hardware joins your fleet without manual intervention, at any scale.
Full machine lifecycle management
Provision, upgrade, repurpose, and decommission hardware from one platform. No more fragmented tooling across lifecycle stages.
Hard network isolation, per tenant
Powered by Netris: hardware-enforced multi-tenancy with programmatic VLANs, VRFs, ACLs, and DPU policies provisioned across your full fabric. Hard network boundaries, zero manual ops.
After the first supplier onboarding, the playbook repeats. New GPU capacity reaches your platform faster, with less engineering involvement every time.
One operational model across all compute tiers means shared tooling, shared expertise, and shared upgrade cycles. Your platform team’s work compounds instead of fragmenting.
Source cheaper GPU capacity from AI clouds or bare metal alongside public cloud and manage it all through one control plane. Your cost per inference request drops without adding ops complexity.
Helping teams unify distributed GPU infrastructure and onboard new compute sources in hours, not months.
Nebius uses vCluster to unify its distributed inference platform and wire new AI cloud suppliers directly to its Token Factory inference gateway.
More AI cloud provider deployments than anyone else. That accumulated knowledge comes with every engagement.
We go deep on your infrastructure, goals, and constraints, so what we build is shaped around what you’re actually trying to run, not a generic template.
We stand up a resilient, scalable platform on your infrastructure within a single day. Not a pilot. Not a POC. Production.
A Slack message or a call is all it takes. Our team is directly reachable to debug, troubleshoot, and resolve issues alongside you.
Every support ticket and deployment feeds back into the platform. When you partner with vCluster, you get the accumulated knowledge of every AI cloud we’ve worked with.
A blueprint for bringing cloud-grade elasticity and automation to NVIDIA DGX systems.
vCluster and Netris integrate Kubernetes and network automation.
Learn how to deliver enterprise-grade Kubernetes for AI workloads and improve ClusterMAX™ rating.
Accelerate your roadmap with the architecture powering today’s leading distributed inference platforms.
