AI Factories: How to architect bare metal for peak performance

Are your AI initiatives constrained not by models—but by infrastructure inefficiency?

As organizations invest heavily in GPUs to build AI Factories, a hidden bottleneck is emerging. Hardware failures, slow reprovisioning, and manual bare metal operations silently erode GPU availability, delay workloads, and undermine ROI. While Kubernetes orchestrates workloads, it cannot recover failed hardware, fix firmware drift, or rapidly repurpose physical servers. At scale, these gaps translate directly into lost AI output.

This 30-minute webinar examines why bare metal automation has become a first-order performance lever for AI infrastructure. Join us to learn how treating physical servers as programmable, cloud-like resources enables higher GPU utilization, faster recovery, and more predictable AI operations. We will introduce Canonical MAAS (Metal-as-a-Service) as the foundation for modern, scalable AI infrastructure.

In this session, you will learn:

• How operational bottlenecks are the main drivers of GPU unavailability

• Why GPU scarcity is often an operations problem, not a supply problem

• How poor hardware lifecycle management directly impacts AI performance and ROI

• The limitations of Kubernetes when bare metal is fragile or manually managed

• How MAAS automates the full bare metal lifecycle: from discovery and commissioning to deployment, HW testing, recovery, and repurposing

• Practical examples of accelerating AI platforms by reducing provisioning and recovery times and increasing effective GPU capacity

If you are responsible for funding, designing, or operating AI infrastructure, this webinar will help you understand where AI ROI is truly won or lost—and how to regain control of your most expensive assets.

Register now to learn how bare metal automation enables more reliable AI operations and higher utilization of GPU infrastructure.