Operate Kubernetes across data centers and clouds. vMetal orchestrates supported infrastructure, and vCluster Platform manages separate tenant environments with dedicated Private Nodes across locations.
Running GPU workloads across on-prem and cloud exposes three gaps.
Namespaces are too weak between GPU tenants, and separate clusters in every location are expensive and slow to provision.
On-prem and cloud GPUs end up in separate silos, which makes consistent tenant management, quotas and billing hard.
Isolating tenants with a VM each adds a layer between workload and GPU. Tenants pay for GPUs and expect close to bare metal performance.
vCluster Platform manages tenant environments across locations. Each Kubernetes tenant has its own control plane and dedicated Private Nodes; vMetal orchestrates supported machines while networking, data placement and failure domains remain deployment decisions. Lintasarta runs 170+ tenant clusters in production.
The parts of a hybrid GPU cloud, from provisioning and tenant isolation to cross-region management and AI stacks.
Each tenant has an independent Kubernetes API, data store and RBAC boundary. Lightweight control-plane hosting reduces dedicated server requirements for distributed GPU infrastructure; Private Nodes keep production workers tenant-specific.
Manage distributed GPU infrastructure across supported clouds and data centers through one platform. Tenant control planes remain separate; plan worker placement, interconnects, data residency and failure domains for each location.
vMetal exposes one Machine API above bare metal and VM provisioning drivers. Registered inventory, images and credentials enable repeatable machine lifecycle workflows for distributed GPU infrastructure. Network automation uses supported integrations such as Netris.
vNode uses Linux user namespaces and seccomp to restrict workload privileges and system calls. It adds runtime hardening for distributed GPU infrastructure without a guest kernel or hypervisor, complementing dedicated workers rather than allocating GPUs.
Use supported workload templates for distributed GPU infrastructure, including the NVIDIA Run:AI partner integration. Configure GPU, network and storage prerequisites, and validate the selected template for Private Nodes before offering it to production customers.
This isn’t a side project. Behind every vCluster deployment is 5+ years of deep K8s engineering, security hardening, and battle-tested infrastructure work at massive scale.
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vCluster Platform can coordinate tenant environments across supported clouds and data centers. Each Kubernetes tenant has its own control plane; a central fleet interface does not mean one tenant API or one failure domain. Plan worker placement, routing, storage and data residency for each location. An optional encrypted VPN can connect control planes and workers where appropriate for the deployment.
Every tenant has its own API server, data store, RBAC and CRDs wherever its workloads run. Private Nodes are the recommended production model, and internal dev, test and CI clusters can run on shared nodes. vNode adds a workload boundary with Linux user namespaces and seccomp. On-prem, hardware network isolation with VLAN, VXLAN and VRF comes through the Netris integration.
Private Nodes are worker nodes joined to one tenant cluster, with that tenant's own CNI and storage configuration. They can be physical machines or supported VMs. Use dedicated bare metal when the service requires exclusive physical servers. vMetal can provision the underlying machines, while platform policies define which capacity a tenant may request and how it is released.
vMetal exposes a stable Machine API above infrastructure-specific drivers for bare metal and VMs. Drivers handle supported provisioning mechanics such as imaging, registration and cleaning. Operators configure inventory, credentials and images before automation runs. vCluster can then use provisioned machines as dedicated Private Nodes, connecting the infrastructure lifecycle to the tenant cluster that needs the capacity.
Boost Run went from decision to production launch in under 45 days for its managed Kubernetes service. That is a customer example rather than a promised implementation time. Your launch depends on machine inventory, driver configuration, networking, storage, templates and service integrations. vMetal and vCluster connect machine orchestration with tenant cluster delivery, reducing the infrastructure workflows you need to build yourself.
vCluster is a CNCF-certified Kubernetes distribution and exposes standard Kubernetes APIs in tenant environments. This supports familiar clients, Helm charts and cluster-scoped resources such as CRDs. Certification covers Kubernetes conformance rather than an entire AI platform or customer deployment. Validate the selected version, networking, storage, GPU drivers and runtime integrations for the workloads you plan to support.
See how vCluster runs tenant clusters across on-prem and cloud GPU infrastructure.
