Architecting highly resilient AI Fabrics: A Blueprint for Next-Gen Data Centers

The fast-growing advancement in AI technologies has resulted in huge loads on the data center architecture resulting in the need to create extremely resistant, and fault-tolerant AI fabrics. This paper looks at AI design principles and technologies necessitated in the construction of fault-tolerant AI infrastructures that can support complex, data-heavy workloads. The major technologies of VXLAN EVPN, RDMA and ultra-low latency interconnect like RoCEv2, NV Link and PCIe Gen5 are paramount to high availability, low latency and high throughput. This article reviews industrial best practice by observing reference architecture of industry leaders like NVIDIA DGX, Meta RSC, AWS Triennium, and reflects on practical approaches in developing a robust fabric of AI computing. The article offers an in-depth road map of how next-gen AI data centers should be designed by paying attention to failure domains, fault tolerance and optimization of convergence. Such robust AI frameworks play a pivotal role by facilitating scalable performance of AI models, inference and training.