AI-Driven Resource Allocation: Revolutionizing Cloud Infrastructure Management
DOI:
https://doi.org/10.32628/CSEIT251112194Keywords:
Cloud Resource Management, Artificial Intelligence, Machine Learning Optimization, Multi-cloud Architecture, Automated ScalingAbstract
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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