Evaluate a Mirantis alternative for your GPU infrastructure. vMetal manages machines, and vCluster combines separate tenant control planes with dedicated production workers through Private Nodes.
GPU infrastructure needs repeatable tenant environments, dedicated worker capacity and fleet operations that fit the service.
Selling GPU capacity means creating a new isolated cluster whenever a customer signs, without a full cluster build each time.
Namespace-level models share control plane components across tenants. Paying customers need their own control plane and their own nodes.
If every customer is a separate physical cluster, upgrades, monitoring and backups grow with every tenant you add.
vCluster supplies separate Kubernetes tenant control planes and dedicated workers through Private Nodes. vMetal orchestrates the underlying machines, and vNode can add runtime hardening for supported workloads. vCluster Labs serves 50+ GPU clouds & Fortune 500s.
vCluster covers bare metal provisioning, tenant cluster orchestration and workload isolation in one stack.
Each tenant has an independent Kubernetes API, data store and RBAC boundary. Lightweight control-plane hosting reduces dedicated server requirements for GPU infrastructure evaluation; Private Nodes keep production workers tenant-specific.
vMetal exposes one Machine API above bare metal and VM provisioning drivers. Registered inventory, images and credentials enable repeatable machine lifecycle workflows for GPU infrastructure evaluation. Network automation uses supported integrations such as Netris.
Private Nodes dedicate worker capacity to one tenant cluster, with its own CNI and storage configuration. For GPU infrastructure evaluation, select physical servers or VMs according to the required infrastructure boundary.
vNode uses Linux user namespaces and seccomp to restrict workload privileges and system calls. It adds runtime hardening for GPU infrastructure evaluation without a guest kernel or hypervisor, complementing dedicated workers rather than allocating GPUs.
Use supported workload templates for GPU infrastructure evaluation, 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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Evaluate vCluster against the service you need to deliver: separate tenant Kubernetes APIs, dedicated production workers and infrastructure lifecycle operations. Private Nodes provide the recommended customer worker model, while vMetal orchestrates machines and Platform coordinates templates and access. Compare documented versions and configurations directly; an embedded runtime alone does not describe every capability of another vendor's platform.
vCluster Labs software powers 100K+ GPUs and 1M+ CPUs, serving 50+ GPU clouds & Fortune 500s combined. In production, Lintasarta operates 170+ tenant clusters, while Boost Run completed its managed Kubernetes launch in under 45 days from the decision. These named deployments provide scale and launch examples for teams evaluating the platform for their own infrastructure.
vCluster Standalone runs as a Kubernetes binary directly on Linux without requiring another Kubernetes cluster, k3s or kubeadm. It can provide an initial Kubernetes foundation. vMetal is a separate infrastructure orchestration layer that requires vCluster Platform and a connected Kubernetes cluster for its Metal3/Ironic path. Hardware registration, images, credentials and driver setup remain prerequisites for machine provisioning.
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.
Supported plans include air-gapped deployment and FIPS features. Private Nodes, tenant-scoped access and optional network segmentation provide controls you can include in a regulated deployment. Select supported images and configurations, and validate the full environment against your requirements. These capabilities do not establish certification of the customer's service, application, hardware or operational procedures.
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.
See how GPU clouds run isolated tenant clusters on Private Nodes with vCluster.
