Are there multi-tenant Baremetal GPU provisioning platforms?

Yes—several platforms specifically solve multi-tenant bare-metal GPU provisioning, and the space has matured a lot recently.

Purpose-built platforms:

• vCluster (vCluster Labs) is the most prominent example. It

gives each tenant their own CNCF-certified Kubernetes API server, etcd, and RBAC running as lightweight pods — no additional physical servers required
, and
has been proven across 100K+ GPU nodes and 50+ GPU clouds
. Their stack is actually three layered products:

• vMetal handles the bare-metal layer:

automatically provision servers with PXE boot, OS installation, and machine registration
, and
automates VLAN and VXLAN networking for secure, hard multi-tenant environments
.

• vCluster (control-plane virtualization) —

Auto Nodes acts as bare metal Karpenter — automatically provisioning GPU servers via Terraform when tenants schedule workloads
.

• vNode (kernel-level isolation, private beta) —

uses seccomp, cgroups, namespaces, and AppArmor to isolate workloads at the kernel level for container breakout protection at bare metal GPU performance, no hypervisor required
.
Together,
vMetal works together with vNode and vCluster to create a unified, programmable platform for AI infrastructure, enabling hard multi-tenancy across networking, nodes, and Kubernetes clusters
. Docs: vmetal.ai and vcluster.com

Enterprise-grade Kubernetes distros as an alternative path:

• Standard bare-metal Kubernetes distributions (k3s, k0s, kubeadm, Talos, RKE2, OpenShift) can be configured for multi-tenancy, though

k3s and Rancher weren't designed for the isolation requirements of untrusted GPU workloads from multiple tenants
. See comparison: vcluster.com

Real-world deployment pattern:

• Mirantis describes a real-world case where

a cloud service provider runs ~150 tenants on shared bare metal, with conventional tenants using namespace-per-customer isolation while AI tenants require more: GPU partitioning via NVIDIA MIG to prevent cross-tenant GPU memory access, plus DPU-enforced VLAN isolation
. More: mirantis.com

Key tradeoff to know: building this yourself is expensive —
building a GPU cloud platform yourself takes 6 to 10 engineers, 6 to 12 months, and over a million dollars
, which is why turnkey platforms like vCluster/vMetal have gained traction versus DIY Kubernetes+bare-metal stacks.