As AI platforms scale into large 'AI Factories,' operational complexity at the hardware layer becomes the primary bottleneck. GPU accelerators are expensive and their downtime directly impacts ROI, yet hardware failures, driver issues, and configuration drift are routine at scale. Bare metal automation addresses this by enabling automated provisioning, lifecycle management, and recovery of physical servers without manual intervention. Canonical MAAS is presented as a solution that treats physical servers as cloud-like programmable resources, integrating with Kubernetes and Juju for full-stack orchestration. Key capabilities include out-of-band BMC-based lifecycle control (discovery, commissioning, deployment, repurposing), hardware validation before production use, and Infrastructure as Code support via Terraform.
Table of contents
Operational challenges in modern AI infrastructureAI Factories: cloud-native software, bare metal hardwareThe role of bare metal automation in AI infrastructureCanonical MAAS as a foundation for AI Factories operationsInfrastructure operations and return on investmentFurther reading and next stepsSort: