Capabilities
The following capabilities are supported as part of the Bare Metal GPU Servers
| Capability | Description |
|---|---|
| Multi-GPU Support | Enables usage of nodes with 1, 4, or 8 high-performance GPUs for scale-out training and inference workloads. |
| Kubernetes Integration | Supports Kubernetes-native workflows; users can deploy workloads using standard manifests and Helm charts. |
| Custom OS Images | Ability to boot bare metal nodes with pre-approved base operating systems such as Ubuntu 22.04 LTS. |
| GPU Sharing (Optional) | Offers full node access, but can also support GPU sharing configurations when enabled at cluster level. |
| High-Speed Interconnects | Nodes are equipped with NVLink, NVSwitch, and NDR Infiniband for high-bandwidth GPU-to-GPU communication. |
| Dedicated CPU Nodes | Allows provisioning of CPU-only nodes for non-GPU workloads such as orchestration, preprocessing, or storage. |
| User-Controlled Lifecycle | End users can start, stop, and terminate nodes through self-service controls with quota enforcement. |
| Custom Initialization Hooks | Supports bootstrap scripts and environment-specific initialization logic. |
| Telemetry & Monitoring | Integration with monitoring dashboards and system metrics for observability (requires setup). |
| Networking & Security | Supports workload isolation through Kubernetes namespaces, CNI-based policies, and secure ingress/egress. |
| No Virtualization Overhead | Direct access to hardware ensures maximum performance for demanding AI/ML pipelines. |