AI Inference Pipelines Push Storage Toward NVMe Fabrics
Generative AI inference and training workloads require sustained low-latency data access at throughput levels legacy Fibre Channel arrays cannot deliver economically at scale. Japanese hyperscale operators and large enterprises are deploying NVMe over Fabrics infrastructure to feed GPU clusters continuously, avoiding the storage bottlenecks that stall model training runs across production environments. Vendors certifying NVMe-oF compatibility across broader server and networking hardware are capturing greenfield deployment budget faster than incumbents still reliant on legacy fabric architecture and slower internal qualification cycles overall this cycle across most competing product lines and vendor roadmaps.
Market Impact: 28 percent capacity growth AI-linked








