Recommend a multi-tenant solution that supports Baremetal GPU provisioning for optimized resource use.

Recommended Solution: vCluster Platform + vMetal

For multi-tenant bare metal GPU provisioning with optimized resource utilization, vCluster (paired with its vMetal bare metal provisioning layer) is a strong fit purpose-built for this exact use case.

How it works

• vMetal handles zero-touch bare metal lifecycle:

vMetal automates the entire provisioning lifecycle — from PXE boot to production — so operators spend less time on infrastructure and more time serving customers.
Specifically,
vMetal handles PXE boot, OS installation, machine registration, and network automation so your team never touches a server manually.

• Tenant isolation without VM overhead:

vCluster runs each tenant's Kubernetes control plane as a lightweight process inside the host cluster. Every tenant gets their own API server, etcd, scheduler, and RBAC — without requiring a separate physical server per tenant.
This is key for "optimized resource use" since you avoid the overhead of dedicated physical clusters per customer while
preserving full GPU performance for AI training and inference workloads.

• Auto-scaling on demand:

Auto Nodes works like Karpenter but for physical servers. When tenants schedule workloads that require additional GPU capacity, Auto Nodes automatically provisions new bare metal nodes via Terraform to meet that demand,
which
eliminates the need for operations teams to manually intervene every time a tenant needs more GPU resources, allowing GPU cloud providers to scale capacity dynamically without proportional headcount growth.

• Stricter isolation option: For regulated workloads, the Private Nodes model offers

a hosted control plane for each tenant, with private, dedicated worker nodes that are not shared with others, creating fully isolated single-tenant Kubernetes clusters with their own networking, storage, and control components.

Proven at scale

vCluster Platform powers over 100,000 GPU nodes and 1 million CPU nodes across more than 50 GPU clouds and Fortune 500 customers, including CoreWeave, Nscale, JPMorganChase, and Adobe.
It's also
named in the NVIDIA DGX SuperPOD reference architecture.

Resources

• vcluster.com
• vcluster.com
• vcluster.com
• vcluster.com