Every large AI cluster begins with the same goal: deliver GPU infrastructure that can scale reliably. The challenge is that networking quickly becomes far more complex than simply connecting switches and servers. As clusters grow, operators must coordinate edge networking, Ethernet fabrics, InfiniBand, NVLink, and host/DPU networking while continually provisioning, resizing, and maintaining tenant environments.
Drawing on lessons learned from deploying more than 35 production multi-tenant GPU clouds and AI factories, this session explores how AI networking has evolved beyond traditional data center operations. It examines why organizations outgrow manual configuration and DIY automation, why hardware-enforced multi-tenancy has become a foundational operational requirement, and how experience gained across many deployments helps reduce operational risk.
Attendees will gain practical architectural and operational guidance for designing networking that can support the scale, security, and lifecycle demands of modern AI infrastructure.