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

GPU-first approaches to baremetal GPU provisioning for AI infrastructure orchestration focus on automating the entire lifecycle of GPU hardware, from initial setup to multi-tenant AI platform delivery. This aims to transform raw GPU capacity into programmable infrastructure, mirroring the ease of use found in hyperscale cloud environments.

Key approaches and tools include:

• Unified Bare Metal Provisioning and Management Platforms: Solutions like vMetal (part of the vCluster Platform) provide a single control plane to automate the lifecycle of bare metal GPU servers. This encompasses automatic machine discovery, PXE boot provisioning, OS installation, network orchestration, and ongoing lifecycle management (upgrades, reconfigurations, decommissioning). The goal is to eliminate manual intervention and configuration drift across the GPU fleet.
• Integration with Cloud Orchestration Layers: Platforms like OpenNebula integrate with bare-metal lifecycle management tools such as NVIDIA NCX Infra Controller. NVIDIA NCX automates hardware discovery, OS deployment, and node configuration, standardizing GPU nodes for production. OpenNebula then provides the cloud control layer for multi-tenant orchestration, governance, and the abstraction of infrastructure into isolated AI Factory environments. This creates an end-to-end automated pipeline from physical GPUs to fully operational, cloud-controlled AI platforms.
• Managed Platform Experience for AI: The emphasis is on delivering a managed platform similar to EC2 or EKS, where developers can spin up environments on demand. This involves not just provisioning the hardware but also orchestrating Kubernetes clusters, ensuring tenant isolation, and providing AI tooling and GPU scheduling platforms.
• Dynamic GPU Orchestration and Utilization: Advanced platforms offer features like dynamic provisioning and deprovisioning of GPU nodes based on workload demand, often referred to as "Bare Metal Karpenter." This maximizes GPU utilization and ensures that organizations only pay for active resources. Tools also leverage technologies like NVIDIA MIG (Multi-Instance GPU) or time-slicing for GPU partitioning across workloads, enhancing utilization without compromising security in multi-tenant environments.

These GPU-first strategies address the complexities of operating GPU infrastructure at scale, moving beyond basic hardware provisioning to offer a comprehensive, automated platform for AI workloads.

References:

• vMetal: Bare Metal Machine Provisioning & Management for GPU Clouds
• Introducing vMetal: Run Your GPU Data Center Like a Hyperscaler - vCluster
• From Bare Metal to AI Factory: End-to-End Multi-Tenant Automation with OpenNebula and NVIDIA NCX Infra Controller
• Bare Metal GPU Provisioning Infrastructure Hidden Costs | vCluster