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eISSN: 2581-9615 || CODEN (USA): WJARAI || Impact Factor: 8.2 || ISSN Approved Journal

Intelligent cloud automation: Leveraging AI and machine learning for enhanced cloud management

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Venkatesh Kata *

CGI, USA.

Review Article

World Journal of Advanced Research and Reviews, 2025, 26(01), 295-301

Article DOI: 10.30574/wjarr.2025.26.1.1094

DOI url: https://doi.org/10.30574/wjarr.2025.26.1.1094

Received on 26 February 2025; revised on 03 April 2025; accepted on 05 April 2025

Artificial Intelligence and Machine Learning are fundamentally transforming cloud computing infrastructure, introducing unprecedented capabilities for intelligent, adaptive, and autonomous system management. This article delves into the profound technological metamorphosis occurring in computational ecosystems, highlighting the transition from static, predetermined infrastructure models to dynamic, self-optimizing environments. Intelligent cloud automation represents a revolutionary paradigm that enables predictive maintenance, sophisticated resource allocation, and autonomous problem resolution. By integrating advanced machine learning algorithms, quantum computing principles, and probabilistic computational models, cloud infrastructures can now anticipate, respond, and optimize themselves with minimal human intervention. The article illuminates the complex technological landscape where neural network architectures, reinforcement learning, and anomaly detection systems converge to create intelligent computational platforms that transcend traditional management approaches.

Artificial Intelligence; Cloud Automation; Machine Learning; Predictive Analytics; Autonomous Infrastructure

https://journalwjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-1094.pdf

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Venkatesh Kata. Intelligent cloud automation: Leveraging AI and machine learning for enhanced cloud management. World Journal of Advanced Research and Reviews, 2025, 26(01), 295-301. Article DOI: https://doi.org/10.30574/wjarr.2025.26.1.1094.

Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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