Your AI Factory Is a Data Pipeline: Where PowerScale, PowerFlex, vSAN, Object Storage, and Local NVMe Belong

This article argues that an AI factory is fundamentally a data pipeline, not a single workload, and that choosing a single storage platform for all AI tasks leads to poor performance and high costs. It provides a practical placement model for different storage types: PowerScale NFS for shared concurrent access, PowerFlex/vSAN for low-latency platform state, object storage for durable artifacts, and local NVMe for disposable scratch data. The article emphasizes classifying data by mutability, sharing, I/O shape, and lifecycle to design effective storage policies, and warns against treating AI storage as a one-size-fits-all category. It is highly relevant to IT/technology, specifically AI infrastructure and storage architecture.