Single-tenant AI inference means each customer's models run where no other customer can reach them. vCluster gives every inference customer a separate tenant cluster on Private Nodes, with vNode and Netris to tighten runtime and network boundaries.
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.
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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.
Residency depends on where you place the platform, tenant clusters, storage, networking and inference services, so the architecture must be set up for the required jurisdiction. vCluster Platform supports air-gapped deployments and FIPS features on supported plans, and Polarise uses it to enforce 100% data residency at the infrastructure layer.
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.
Tenant clusters come up in minutes, not hours; QumulusAI spins up isolated Kubernetes environments in about 1 minute. When Private Nodes must be provisioned rather than assigned from existing capacity, the infrastructure driver sets the pace.
See how vCluster Platform delivers single-tenant AI inference environments with hard tenant isolation.
