GPU-aware scheduling
NVIDIA device discovery and the nvidia.com/gpu resource are configured on a labeled RTX 3090 node pool.
Managed Kubernetes · GPU node pool
Ship GPU workloads.
Skip cluster operations.
A managed Kubernetes workspace backed by an NVIDIA RTX 3090 GPU pool in Frankfurt. Use standard kubectl, Jobs, Deployments, Secrets, and persistent volumes while BHK Cloud runs the control plane.
Checking launch capacity…
$ export KUBECONFIG=bhk-ml-prod.yaml $ kubectl apply -f gpu-job.yaml job.batch/model-trainer created $ kubectl get pod NAME READY STATUS GPU model-trainer 1/1 Running 1 ✓ NVIDIA RTX 3090 · 24 GB VRAM
The managed layer
Production guardrails are provisioned with every workspace.
Tenant isolation
Each customer receives a dedicated namespace, service account, scoped RBAC, default network policy, and no cluster-admin access.
Predictable limits
ResourceQuota and LimitRange policies cap each workspace at one GPU, 12 vCPU, 48 GiB RAM, 200 GiB storage, and 20 pods.
Standard Kubernetes API
Use kubectl, Helm, Terraform, GitOps, or any Kubernetes client. Download a short-lived kubeconfig from your dashboard.
Managed control plane
BHK Cloud handles the Kubernetes server, container runtime, GPU plugin, certificates, and platform updates.
Built for AI workloads
Run model training, fine-tuning, batch inference, rendering, and CUDA-enabled container jobs without managing a node.
Launch plan
Managed RTX 3090 workspace
$0.25/GPU hour
A $0.10/hr managed-service premium over raw GPU compute. No upfront charge with Buy Now Pay Later. Usage is billed while GPU workloads run.
1× RTX 309024 GB VRAM
12 vCPUworkspace quota
48 GiBworkspace memory
200 GiBpersistent storage quota
Launch capacity is currently limited. Multiple workspaces can be provisioned; GPU pods queue safely when the physical GPU is occupied.
Self-service onboarding
From account to CUDA job in four steps.
Create an account
Sign in to the BHK Cloud customer dashboard. No manual infrastructure ticket is required.
Provision a workspace
Name the workspace and launch the Managed RTX 3090 plan from the Kubernetes tab.
Download kubeconfig
Get a namespace-scoped kubeconfig with a 24-hour token. Generate a fresh file whenever needed.
Deploy your container
Apply the GPU Job example, follow logs with kubectl, and delete finished workloads to stop GPU usage.
Managed GPU Kubernetes
Keep the Kubernetes API. Hand off the operations.
Launch an isolated workspace at $0.25 per GPU hour or contact us for reserved nodes, additional GPUs, private networking, and custom quotas.
Launch workspace → Discuss reserved capacity