AI-Driven Resource Allocation: Revolutionizing Cloud Infrastructure Management

Authors

  • Sushant Sood Microsoft, USA Author

DOI:

https://doi.org/10.32628/CSEIT251112194

Keywords:

Cloud Resource Management, Artificial Intelligence, Machine Learning Optimization, Multi-cloud Architecture, Automated Scaling

Abstract

This comprehensive article examines the transformative impact of artificial intelligence on cloud resource management, exploring the evolution from traditional static allocation methods to dynamic, AI-driven approaches. The article investigates core technologies, including machine learning models and real-time decision-making frameworks, while evaluating their applications across virtual machine provisioning, container orchestration, and multi-cloud environments. Through detailed case studies of e-commerce platforms and video streaming services, the article demonstrates significant improvements in resource utilization, cost optimization, and service reliability. The article further addresses technical and operational challenges, including model overhead and system complexity, providing insights into the implementation considerations for organizations adopting AI-driven cloud management solutions.

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References

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Published

03-02-2025

Issue

Section

Research Articles

How to Cite

AI-Driven Resource Allocation: Revolutionizing Cloud Infrastructure Management. (2025). International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 11(1), 1652-1662. https://doi.org/10.32628/CSEIT251112194