Standardize Kubernetes across public cloud, AI clouds, on-prem, edge, GPU, and CPU. Operations stay the same no matter where compute is supplied, and workloads shift between environments without re-architecting.
You need a unified operating layer, not a different Kubernetes stack for every cloud, every region, and every data center.
EKS, GKE, AKS, OpenShift, vanilla on-prem, k3s at the edge. Each ships with its own tooling, upgrade path, and security boundary. Nothing transfers. Expertise stops at every fence.
Most platform teams building a unified Kubernetes layer are still mid-project two years in. Scope expands faster than the team can ship.
Share one control plane and tenants see platform internals. Dedicated cluster per tenant means a dedicated control plane for every one. Neither holds in production.
vCluster standardizes your entire estate under one operating model. Same playbook. Every environment. Every time.
One ops team. Every environment. Zero per-provider tooling.
Internal teams, customer-facing workloads, regulated business units. They get a clean Kubernetes environment. Your platform stays hidden, protected, and stable.
vCluster delivers the operating layer for hybrid Kubernetes: from the bare metal underneath, up through tenant-isolated workload environments, across every compute source. Each product works independently or as a unified platform.
Blocks container escapes at the node level
Each tenant workload runs in a dedicated kernel boundary. The compromise of one tenant doesn’t reach another, and it doesn’t reach the platform.
Container-native, no hypervisor tax
No micro-VM, no syscall interception. Bare metal GPU and CPU performance preserved. Works on bare metal, cloud, and any Kubernetes.
Drop-in alternative to gVisor and Kata Containers
Pairs naturally with vCluster tenant clusters for defense-in-depth. Hardens control plane pods and tenant workloads against compromise.
Provision tenants across managed services and bare metal
One platform to manage tenants across EKS, GKE, AKS, and private cloud. Developers get the same experience regardless of infrastructure.
Tenant clusters for any tenant in production
Developer, team, customer, workload, machine, or service. Each tenant gets its own dedicated API server, etcd, and RBAC. The platform itself stays abstracted away.
Shift workloads freely across the estate
Workloads move between public and private cloud, between DCs, and between GPU and CPU tiers without re-architecting.
Zero-touch bare metal provisioning
PXE boot and OS configuration happen automatically. Declare bare metal nodes as Kubernetes resources. Hardware failures trigger automatic reprovisioning.
Full machine lifecycle, one platform
Provision, patch, repurpose, and decommission hardware from one platform. No more fragmented tooling across lifecycle stages.
Karpenter-compatible bare metal autoscaling
Bare metal nodes scale with workload demand, same model as your cloud fleet. The missing piece for bringing private capacity into the same operating model as public cloud.
EKS, AKS, GKE, on-prem, edge, GPU racks: all managed through a single control plane with shared tooling. Your platform team’s work compounds instead of fragmenting.
After the first environment is onboarded, the playbook repeats. Standing up production Kubernetes in a new region or DC drops from months to hours.
Internal developers ship to the same Kubernetes interface whether the workload lands on EKS, GKE, AKS, on-prem, or edge. The platform team owns the surface area.
One ops team operates the entire fleet. No per-cloud specialists. No bespoke runbooks. Tooling investment compounds across every compute source instead of being rebuilt for each.
Workloads move between public and private cloud, between DCs, and between GPU and CPU tiers without re-architecting. Repatriation and regional rebalancing stop being multi-quarter projects.
Every tenant gets verifiable isolation, without standing up a dedicated cluster for each one. The audit story is the same regardless of where the workload runs.
Distributed footprints. Regulated workloads. Already running hybrid Kubernetes, and looking to standardize it.
Multi-cloud across AWS, Azure, GCP. Owned DCs for trading and risk. Regional data residency on every workload.
Factory floor edge. Manufacturing and R&D under different residency rules. Multi-cloud and on-prem across EU, US, and China.
HIPAA, regional health data laws, clinical trial residency. R&D running AI on owned GPU capacity.
Sovereign cloud, non-negotiable. In-country residency on every workload. Production spanning classified networks, civilian cloud, and on-prem.
Stop running five Kubernetes flavors in production. Get one operating layer across every compute source, with the tenant isolation and workload portability your estate already needs.
