Automated cost optimization for cloud infrastructure with generative AI: A technical deep dive

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.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-04-14
DOI
https://doi.org/10.30574/wjaets.2025.15.1.0292
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

Automated cost optimization for cloud infrastructure with generative AI: A technical deep dive

Vijayakumar Jayaseelan
World Journal of Advanced Engineering Technology and Sciences
Big Data and Business Intelligence
article

Automated cost optimization for cloud infrastructure with generative AI: A technical deep dive

Vijayakumar Jayaseelan
article en

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.

World Journal of Advanced Engineering Technology and SciencesVol. 15(1)
Openalex Percentile: Top 89%
Big Data and Business Intelligence
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