Your competitors are already selling managed Kubernetes. Your customers are already asking for it. vCluster gives you the complete platform stack to launch in days, not quarters, without hiring a team of Kubernetes experts or building from scratch.
Customers don’t just want raw compute. They want the cloud experience — managed Kubernetes, self-service environments, and tooling they already know. AI cloud providers winning today are the ones who figured that out first.
GPU specs are converging. The providers who escape the pricing war are the ones who give customers a reason to stay beyond raw performance.
GPU providers who sell wholesale to hyperscalers hand over the customer relationship and the margin. The ones building durable cloud businesses own the experience directly.
AI teams have used AWS and GCP. They expect self-service environments, managed Kubernetes, and cloud-native tooling, and they'll go back to a hyperscaler if you can't deliver it.
CoreWeave spent years building their Kubernetes platform. AWS built EKS over a decade. You don’t have that time, and you shouldn’t need it.
AI infrastructure needs something purpose-built. The three categories of alternatives all fall short in different ways.
Requires stitching Kubernetes, custom tooling, and homegrown isolation together. Most teams are still building two years in.
Heavy enterprise platforms designed for traditional apps. Not architected for AI workloads, bare metal, or GPU-native multi-tenancy.
Limited real-world deployments and production track record. You don’t want to be the reference customer that proves their tech works.
Trusted by leading AI cloud providers, powering 100K+ GPUs.
vCluster delivers the complete infrastructure stack for AI cloud providers, from bare metal provisioning up through tenant Kubernetes environments and ready-to-run AI/ML application stacks. Each layer is production-proven and works independently or as a unified platform.
Pre-configured environments, deployed in minutes
Deploy platforms like Run:AI, Ray, and Jupyter with production-ready defaults. From cluster to live AI/ML stack in minutes, not months.
Consistent experience across every tenant
Every customer gets the same environment, policies, and infrastructure configuration, no manual setup, no configuration drift.
The cloud experience on your infrastructure
Give customers the self-service, turnkey platform experience they expect from hyperscalers, running directly on your GPU data center.
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 AI and agentic workloads
Designed for dynamic code execution, package installs, and root access, safely. Built for the realities of AI inference and agent runtimes.
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.
Boost Run launched a production-grade managed Kubernetes service in under 45 days with zero new platform engineering hires.
Charge premium for managed Kubernetes. Support more tenants on the same hardware. Unlock usage-based and per-cluster pricing models.
Customers who want the AWS experience won’t wait. Deliver it before your competitors do, before the hyperscalers get there on your turf.
Virtual clusters eliminate per-customer cluster overhead. Add hundreds of isolated tenants without adding headcount.
Built-in Day 2 operations: observability, updates, backups, compliance, and config management across your entire fleet.
A Kubernetes experience purpose-built for AI/ML workloads and bare metal performance. Something no hyperscaler can match on your hardware.
Days from decision to production launch
Virtual clusters
in production
GPUs planned for AI supercluster infrastructure
“vCluster is the first proven solution for operationalizing virtual Kubernetes clusters at scale and we continue to be impressed by the vCluster team and the innovations they ship to customers like us.”
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 trusted by today’s fastest-growing AI cloud providers.
