Overview
What is a Private Cluster?
Private Cluster enables you to create a dedicated pool of GPU-backed compute resources that can be shared across multiple projects. The cluster is billed at a fixed price, independent of actual GPU utilization, providing predictable costs and guaranteed capacity.
Once a Private Cluster is created, you can deploy Nodes, Inference Endpoints, Training Clusters, and Vector Databases within it without incurring additional per-service charges.
What this means in practice
| Capability | Benefit |
|---|---|
| Dedicated GPU pool | Guaranteed hardware exclusively for your organization |
| Fixed billing | Predictable costs independent of GPU utilization |
| Multi-service deployment | Nodes, inference, training, and databases at no extra charge |
| Flexible allocation | Distribute and reclaim GPUs across projects dynamically |
| Role-based access | IAM-governed permissions for admins, leads, and members |
Who Should Use a Private Cluster?
Private Clusters are best suited for teams that:
- Run long-running or predictable AI/ML workloads
- Require guaranteed GPU availability
- Want to share GPUs across multiple projects without repeated provisioning
- Prefer fixed and predictable billing
- Need controlled access through role-based permissions
When to Choose a Private Cluster?
Choose a Private Cluster if you want to:
- Avoid GPU shortages during peak demand
- Eliminate per-resource billing for nodes, inference, and databases
- Centrally manage GPU capacity across projects
- Control GPU allocation without deleting workloads
- Reduce operational overhead for large or growing AI organizations
Key Benefits
- Fixed Pricing – Billing is independent of actual GPU usage
- No Hidden Costs – No extra charges for deploying services inside the cluster
- Guaranteed Capacity – GPUs are reserved exclusively for your organization
- Flexible Allocation – Dynamically allocate and deallocate GPUs across projects
- Secure Access Control – Governed by IAM roles and permissions
Private Cluster vs On-Demand Instances
| Feature | Private Cluster | On-Demand Instance |
|---|---|---|
| Billing model | Fixed per node | Per-hour per instance |
| GPU availability | Guaranteed | Subject to inventory |
| Multi-project sharing | Yes | No |
| Services included | Nodes, Inference, Training, VectorDB | Per-instance only |
| Best for | Enterprise, long-running workloads | Short-term, variable workloads |