What a Reference Architecture for Distributed AI Training Actually Looks Like

General-purpose cloud infrastructure struggles with production-scale distributed AI training because failures are structural rather than random. The authors outline a purpose-built reference architecture with four interdependent layers: topology-aware orchestration, checkpoint-optimized storage, high-performance interconnect, and integrated observability. These layers work together to ensure reliability, reduce failure recovery time, and improve overall system efficiency at scale.