Best Practices For Optimizing AI Infrastructure At Scale
F5, Wednesday, January 21st, 2026
Most organizations don't struggle with AI because they lack models; models are proliferating in both number and type. They struggle because their infrastructure was never designed for the way AI moves data.
Training, fine-tuning, and retrieval-augmented generation (RAG) all depend on moving massive volumes of data-reliably, securely, and repeatedly-across storage systems, networks, and compute tiers. As AI initiatives scale, even small inefficiencies in data access, security policy, or resiliency can ripple outward-slowing pipelines, breaking jobs, or driving up infrastructure costs.