Cloud digital twins: Redefining enterprise infrastructure management with predictive analytics and automation

Isaac, Clement Praveen Xavier Pakkam (2025) Cloud digital twins: Redefining enterprise infrastructure management with predictive analytics and automation. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 1496-1515. ISSN 2582-8266

Cloud Digital Twins (CDTs) represent a paradigm shift in enterprise infrastructure management, offering organizations a revolutionary approach to simulate, optimize, and automate complex multi-cloud and hybrid environments. This comprehensive framework creates AI-powered virtual replicas of cloud infrastructure that mirror the behavior, configuration, and performance characteristics of production systems. Through a three-tier architecture encompassing Infrastructure Digital Twins, Policy Digital Twins, and Operational Digital Twins, organizations can anticipate system failures, optimize resource allocation, conduct pre-deployment impact analysis, and simulate disaster recovery scenarios without risking live environments. The significance of this model lies in its novel integration of technical, governance, and operational aspects into a unified framework, addressing the full spectrum of cloud management challenges that traditional approaches handle in isolation. The implementation methodology follows a structured approach: environment assessment, twin creation, integration with existing workflows, and continuous improvement. While offering significant operational benefits, CDTs introduce new security considerations around data synchronization and model drift prevention. As the technology matures, future directions include cross-provider optimization, autonomous operations through reinforcement learning, and edge-to-cloud continuity for unified management of distributed infrastructure. CDTs are becoming essential components of cloud governance strategies for enterprises seeking enhanced resilience, compliance, and operational efficiency.