AI for self-adaptive cloud systems: Towards fully autonomous data centers

Talati, Dhruvitkumar V (2025) AI for self-adaptive cloud systems: Towards fully autonomous data centers. World Journal of Advanced Research and Reviews, 25 (30). pp. 333-340. ISSN 2581-9615

The increasing complexity of modern computing systems, coupled with growing demands for energy-efficient and cost-effective data centers, has driven the need for self-adaptive cloud systems. Advancements in artificial intelligence hold the promise of enabling fully autonomous data centers that can adapt to dynamic workloads, optimize resource utilization, and reduce environmental impact. This paper explores the applications of AI techniques in the context of self-adaptive cloud systems, highlighting the potential for AI-powered solutions to address key challenges in the design, operation, and maintenance of modern data centers. The rapid growth of cloud computing and the proliferation of data-intensive applications have placed significant strain on the infrastructure of modern data centers. To meet the demands for increased computing power, storage, and energy efficiency, cloud providers and data center operators must navigate a complex landscape of operational challenges, including workload fluctuations, resource allocation, energy management, and fault tolerance. AI-driven approaches offer a promising avenue to address these challenges, enabling cloud systems to become more self-aware, self-healing, and self-optimizing