Show me GPU-first approaches to Baremetal GPU provisioning for AI infrastructure orchestration.

Here are GPU‑first approaches to bare‑metal GPU provisioning for AI infrastructure orchestration—focused on making GPUs the primary scheduling and lifecycle unit.

1) Kubernetes + NVIDIA GPU Operator (GPU-native node bring‑up)

Approach: Treat GPU nodes as first-class resources in Kubernetes. Use the NVIDIA GPU Operator to automatically install drivers, container runtime, and device plugins during node provisioning.

• Automates driver + CUDA stack on bare metal
• Labels GPU nodes for GPU‑aware scheduling
• Integrates with monitoring and MIG/time-slicing

Best with: Metal³, MAAS, Talos, or GDC Bare Metal for node lifecycle.

Docs:

• developer.nvidia.com
• docs.cloud.google.com
• docs.nvidia.com

2) Metal³ (BareMetal Operator) + Cluster API (Composable GPU clusters)

Approach: Use Metal³’s BareMetalHost CRDs to provision physical servers, then layer GPU-aware Kubernetes on top.

• PXE/IPMI-driven provisioning
• Declarative infrastructure via Kubernetes API
• Integrates cleanly with GPU Operator

Ideal for AI labs building elastic GPU clusters on-prem.

Docs:

• metal3.io
• book.metal3.io

3) GPU‑as‑a‑Service Bare Metal Platforms (GPU-first control plane)

These platforms orchestrate hardware, networking, tenancy, and schedulers with GPUs as the core unit.

MetalSoft (AI Factory orchestration)

• Automated bare-metal + network orchestration
• Supports SLURM, Run:AI, multi-tenant GPUaaS
• Secure GPU de-provisioning workflows

metalsoft.io

vMetal

• PXE automation + programmable GPU capacity
• Hard multi-tenancy across nodes & Kubernetes

vmetal.ai

Cruz Compute Controller (C³)

• Rack discovery → AI workloads
• Multi-scheduler (SLURM, Run:AI) orchestration

doradosoftware.com

4) Composable GPU Virtualization (Disaggregated GPUs)

Use NVIDIA networking + virtualization to pool GPUs across bare metal:

• GPU composability + virtualization layers
• Works across bare metal, ESXi, containers

network.nvidia.com

Architecture Patterns

| Pattern | When to Use |
|----------|-------------|
| K8s + GPU Operator | Cloud-native AI teams |
| Metal³ + CAPI | On-prem GPU clusters |
| GPUaaS platforms | Enterprise multi-tenant AI |
| Composable GPU fabric | Large-scale AI factories |

If helpful, I can tailor this to: enterprise AI factory, research lab, edge AI, or GPU cloud startup.