MANAGED KUBERNETES

GPU KUBERNETES
AS A SERVICE

A managed K8s control plane with GPU node pools. We handle etcd, upgrades, and monitoring. You deploy with kubectl. Dedicated clusters per customer, no shared infrastructure.

CONTACT SALES

WHY MANAGED KUBERNETES

DEDICATED CONTROL PLANE

Your own API server, etcd, and scheduler. No shared clusters, no namespace-level isolation workarounds. Full cluster-admin access to your dedicated environment.

GPU NODE POOLS

H100, H200, and B200 node pools with NVIDIA device plugin pre-installed. Request GPUs via standard resource limits. Mix GPU and CPU node pools in one cluster.

STANDARD KUBECTL ACCESS

We generate a kubeconfig file. You export it and run kubectl get nodes. Standard K8s workflow with Helm, kustomize, and any tool that speaks the K8s API.

AUTOMATIC RESTARTS

Pods restart on failure automatically. Health checks, readiness probes, and rolling deployments built in. Your inference server stays up without manual intervention.

WE MANAGE THE INFRA

etcd backups every 6 hours. K8s version upgrades on a managed schedule. Control plane monitoring with alerting. You never touch a master node.

PHYSICAL ISOLATION

Dedicated hardware per customer. IP-whitelisted API server on port 6443. No shared kernels, no shared GPU memory, no shared control plane. Your cluster is yours.

HOW IT WORKS

01

DEFINE NODE POOLS

Tell us how many GPU nodes, which GPU type, and whether you need CPU node pools. We'll confirm hardware availability and timeline.

02

WE BUILD YOUR CLUSTER

We provision master nodes, join your GPU workers, install the NVIDIA device plugin, configure networking, and set up etcd backups.

03

KUBECTL GET NODES

We send you a kubeconfig file. Export it, run kubectl get nodes, and see your GPU cluster ready. Deploy your first workload with kubectl apply.

RAW VMs VS. MANAGED K8S

RAW GPU VMs

  • Manual process restarts on failure
  • No built-in health checks
  • Manual load balancing across machines
  • SSH-based deployments
  • Scaling requires new VM provisioning

MANAGED KUBERNETES

  • Automatic pod restart on failure
  • Health checks and readiness probes
  • Built-in service discovery and load balancing
  • kubectl apply declarative deployments
  • Cluster autoscaler adds nodes on demand

READY FOR GPU KUBERNETES?

Tell us about your workload and we'll design the right cluster for your team.

CONTACT SALES