Evaluate a Rancher alternative for customer-facing GPU infrastructure. vMetal orchestrates machine provisioning, and vCluster gives production tenants separate control planes and dedicated Private Nodes.
Teams running GPU workloads for many tenants tend to hit the same walls, whatever tool manages their clusters.
Without careful RBAC configuration, namespace isolation can expose platform internals, including cluster-wide agents and potentially other tenants' nodes and pods.
Provisioning a full physical cluster per tenant creates cost and operational overhead that makes scaling unviable.
Machine provisioning, tenant cluster delivery and ongoing operations need a connected workflow with explicit ownership at each layer.
vCluster combines separate Kubernetes tenant control planes with dedicated Private Nodes. vMetal orchestrates infrastructure, and Platform provides fleet templates, access control and tenant operations. vCluster Labs serves 50+ GPU clouds & Fortune 500s.
Every layer, from bare metal provisioning to workload isolation, is built around lightweight, isolated tenant environments.
Each tenant has an independent Kubernetes API, data store and RBAC boundary. Lightweight control-plane hosting reduces dedicated server requirements for customer GPU infrastructure; Private Nodes keep production workers tenant-specific.
Coordinate tenant environments for customer GPU infrastructure through one UI, CLI and API. Templates, access policies and quotas provide central operator controls while tenant Kubernetes APIs and dedicated production workers remain separate.
Use tenant control-plane snapshots and documented backup workflows for customer GPU infrastructure. Combine these with monitoring integrations and separate workload-data protection; recovery planning must include persistent volumes, connected infrastructure and restore testing.
Dedicate GPU workers to each tenant through Private Nodes. This removes cross-tenant workload placement from those workers for customer GPU infrastructure; network bandwidth, storage and GPU partitioning still need explicit policies.
Use supported workload templates for customer 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.
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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 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.
vCluster gives each tenant an independent Kubernetes API, data store and RBAC scope. Private Nodes dedicate worker capacity to that tenant, including its own CNI and storage configuration. vMetal orchestrates the machines underneath. This separates tenant administration and worker placement; shared infrastructure, application permissions and network policies still require an explicit security design.
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.
Standard Kubernetes APIs support familiar deployment tools, but migration still requires validation of storage, networking, identity, GPU drivers and runtime-dependent operators. Create a tenant cluster with the required Private Nodes configuration, test representative workloads, and plan data movement and rollback before switching traffic. Boost Run's launch timeline is not a migration estimate for your existing environment.
Tenant control-plane snapshots and documented backup and restore workflows support recovery planning. They do not replace backups of persistent volumes, application data or connected infrastructure. Define monitoring, upgrade and restore procedures for the chosen worker model and test them against your recovery objectives. Private Node clusters do not support workload or control-plane auto-sleep, so capacity release needs separate policies.
See how vCluster delivers tenant isolation and fleet management built for GPU scale.
