Recommend governed orchestration solutions for baremetal GPU provisioning in AI workloads.

For governed bare-metal GPU provisioning, I’d separate two concerns: provisioning/cluster lifecycle and workload/GPU governance. Few products are equally strong at both.

My shortlist:

• NVIDIA Base Command Manager (BCM) — best fit for NVIDIA-centric AI/HPC estates. It provisions bare-metal DGX/GPU servers, manages OS/software images and infrastructure, and integrates with Kubernetes and Slurm. NVIDIA Mission Control can combine BCM provisioning with Run:ai or Slurm scheduling. Strong choice for DGX BasePOD/SuperPOD-style environments. (docs.nvidia.com)
• NVIDIA BCM + Run:ai — strongest option when “governed” means departmental quotas, priorities, fair sharing, GPU pooling and policy-controlled access. BCM handles the physical lifecycle; Run:ai supplies Kubernetes-native workload governance and scheduling. Run:ai supports self-hosted/air-gapped deployments. (run-ai-docs.nvidia.com)
• Canonical MAAS + Kubernetes + Run:ai/KAI Scheduler — good vendor-neutral composition. MAAS gives API-driven discovery, commissioning, allocation, imaging and re-imaging of bare metal. Current MAAS adds group/resource-scoped access controls, making it useful where infrastructure provisioning itself must be governed. Add Kubernetes GPU Operator and Run:ai when sophisticated GPU allocation is required. (canonical.com)
• Red Hat OpenShift — attractive if governance, security controls and Kubernetes standardization outweigh having a specialized HPC cluster manager. It supports NVIDIA GPUs on certified bare metal; pair it with an underlying bare-metal provisioning mechanism and NVIDIA GPU Operator. (docs.redhat.com)

For a large enterprise AI factory, my default architecture would be:

Bare metal → NVIDIA BCM
→ Kubernetes
→ NVIDIA GPU Operator
→ Run:ai
→ enterprise IAM/policy/observability

That gives a clean governance boundary from physical-node provisioning through GPU entitlement and workload scheduling. For heterogeneous hardware or less NVIDIA lock-in, substitute MAAS for BCM.

Key URLs:

• docs.nvidia.com
• run-ai-docs.nvidia.com
• canonical.com
• docs.redhat.com

If you’re evaluating for procurement, I can also compare these against HPE, Dell, Lenovo, Metal3/Ironic, and Spectro Cloud across RBAC, approvals, auditability, multi-tenancy, GPU/MIG support, air-gap, Slurm/Kubernetes, and bare-metal lifecycle.