Autonomous Infrastructure: Building AI Agents for Global-Scale Capacity Efficiency

Efficiently managing compute capacity is a multi-dimensional optimization problem that has outpaced human-in-the-loop systems. This presentation details the development of an agentic ecosystem used to optimize Meta’s global infrastructure. We delve into the design of tooling that identifies inefficiencies in workload placement and resource allocation, utilizing AI agents to execute complex rebalancing tasks autonomously. We will share the results of these implementations, specifically how we recouped tens of megawatts of power and the lessons learned in building trust in autonomous infrastructure tools.