Run each inference customer in an isolated tenant cluster with its own Kubernetes control plane and Private Nodes. vCluster Platform centralizes tenant access, templates, capacity policy, and fleet operations across your GPU infrastructure.
Shared inference infrastructure needs clear tenant boundaries across the control plane, worker capacity, runtime, and network.
Namespace-only designs share control-plane and node-level components between customers.
Shared worker nodes can expose inference workloads to cross-tenant resource contention.
Data residency depends on the placement and configuration of compute, storage, networking, and inference services, not on a single product setting.
vCluster Platform gives each inference customer a separate tenant cluster and uses Private Nodes as the production default. Optional vNode and Netris integrations strengthen the runtime and physical network boundaries.
Single-tenant AI inference combines a separate tenant control plane, Private Nodes, and optional runtime and physical network isolation.
Private Nodes assign dedicated worker capacity, networking, and storage to one production tenant cluster at a time.
vNode uses Linux user namespaces and seccomp filters to strengthen the runtime boundary for inference workloads that need additional isolation.
When Metal3 and Netris are configured, separate tenant network environments can receive hardware-backed L2 isolation.
vCluster Platform supports air-gapped deployments and FIPS features on supported plans for infrastructure operated in controlled environments.
Each inference tenant gets its own virtualized Kubernetes control plane, API server, and RBAC boundary.
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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Namespace-only designs share a Kubernetes API server and node-level components. vCluster gives each inference customer a separate virtualized control plane and RBAC boundary, with Private Nodes as the production default for dedicated worker capacity.
vCluster Platform supports air-gapped deployments and FIPS features on supported plans. Data residency depends on where you deploy the platform, tenant clusters, storage, networking, and inference services, so the architecture must be configured for the required jurisdiction.
No separate Kubernetes control-plane servers are required for every customer. The tenant control plane runs as isolated pods on the control plane cluster, while Private Nodes provide dedicated production worker capacity.
vNode is a tenant isolation container runtime that uses Linux user namespaces and seccomp filters to strengthen the workload boundary. It complements the tenant control plane and Private Nodes without taking responsibility for inference scheduling or GPU allocation.
Yes. One vCluster Platform instance can manage connected control plane clusters across regions and infrastructure environments. Operators retain central control of access, templates, capacity, and observability.
Virtualized control planes are lightweight and can be created quickly. Provisioning time for Private Nodes depends on whether capacity is already available or must be provisioned through a cloud or bare metal driver.
See how vCluster Platform delivers single-tenant AI inference environments with hard tenant isolation.
