International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 73 | Issue 5 | Year 2025 | Article Id. IJCTT-V73I5P121 | DOI : https://doi.org/10.14445/22312803/IJCTT-V73I5P121

Cloud Migration in the GenAI Era: A Technical and Empirical Examination

Vamsi Kuruba

Received Revised Accepted Published
03 Apr 2025 07 May 2025 17 May 2025 31 May 2025

Citation :

Vamsi Kuruba, "Cloud Migration in the GenAI Era: A Technical and Empirical Examination," International Journal of Computer Trends and Technology (IJCTT), vol. 73, no. 5, pp. 166-171, 2025. Crossref, https://doi.org/10.14445/22312803/IJCTT-V73I5P121

Abstract

The rise of large-scale Generative AI (GenAI) applications has placed cloud migration at the forefront of IT and research agendas. Modern organizations recognize the cloud as a natural platform for handling high computational and storage requirements. However, the pathway to successful cloud migration involves complex design decisions, security considerations, and performance trade-offs. This research provides a comprehensive, technical exploration of cloud migration in the GenAI era, supplemented by original empirical benchmarks. Our work examines the fundamental drivers of cloud migration for GenAI, details an extensive methodology for planning and executing cloud infrastructure transformation, and proposes an automated pipeline for on-demand High-Performance Computing (HPC) clusters tailored to large model training. To validate our approach, we present original research comparing different resource provisioning strategies, including container orchestration, ephemeral GPU clusters, and hybrid on-premise/cloud setups, revealing a 20–40% reduction in both training time and infrastructure costs when leveraging container-based HPC clusters. We discuss best practices, future directions, and potential regulatory challenges in GenAI-driven cloud deployments.

Keywords

Generative AI (GenAI), cloud migration, large-scale applications, high-performance computing (HPC).

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