Jayaseelan, Vijayakumar (2025) Automated cost optimization for cloud infrastructure with generative AI: A technical deep dive. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 812-821. ISSN 2582-8266
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Abstract
Automated Cost Optimization for Cloud Infrastructure powered by Generative AI represents a transformative approach to managing and optimizing cloud expenses. This comprehensive article examines how artificial intelligence and machine learning technologies are revolutionizing cloud cost management through automated analysis, prediction, and optimization. The article investigates the challenges organizations face in cloud cost management and demonstrates how AI-driven solutions provide enhanced visibility, improved resource utilization, and automated optimization capabilities. Through analysis of implementation strategies, best practices, and real-world case studies, this article illustrates the effectiveness of AI-powered approaches in achieving sustainable cost optimization while maintaining performance and compliance requirements. The article also explores the integration of FinOps practices, the impact of multi-cloud environments, and the role of automated decision-making in cloud resource management.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjaets.2025.15.1.0292 |
Uncontrolled Keywords: | Cloud Cost Optimization; Generative AI; Finops; Resource Utilization; Automated Infrastructure |
Depositing User: | Editor Engineering Section |
Date Deposited: | 04 Aug 2025 16:01 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/2814 |