Demystifying multi and hybrid cloud AI infrastructure: A beginner's guide to distributed high-performance architecture in hybrid and multi-cloud environments

Patil, Praneeth Kamalaksha (2025) Demystifying multi and hybrid cloud AI infrastructure: A beginner's guide to distributed high-performance architecture in hybrid and multi-cloud environments. World Journal of Advanced Engineering Technology and Sciences, 16 (1). pp. 266-288. ISSN 2582-8266

This article demystifies multi-cloud AI infrastructure, providing an accessible overview of distributed high-performance architectures essential for modern artificial intelligence systems. It explores the fundamental challenges of efficient data transfer between environments, addressing speed limitations, security vulnerabilities, and cost concerns. The discussion examines hybrid and multi-cloud architectures that combine on-premises systems with multiple cloud providers to optimize AI workloads. The article highlights emerging solutions, including direct physical connectivity options, Software-Defined Networking (SDN), and Smart Network Interface Cards (SmartNICs). Through detailed case studies and practical implementation considerations, it reveals how organizations can achieve substantial improvements in performance, security, and cost-efficiency while maintaining regulatory compliance. The article further explores future trends including edge computing for real-time inference and AI-driven network optimization, illustrating how these technologies will shape the next generation of AI infrastructure.