AI-Augmented Predictive Analytics for Proactive Cloud Infrastructure Management

Authors

  • Ravi Chandra Thota Independent Researcher, Sterling, Viginia, USA Author

DOI:

https://doi.org/10.55662/JST.2024.5407

Keywords:

AI-augmented analytics, predictive modeling, cloud infrastructure, anomaly detection

Abstract

Cloud computing environments involvement in advanced management strategies to ensure optimal performance, cost efficiency, and reliability. Predictive analytics based on AI- augmentation is emerged as a transformative approach to proactive cloud infrastructure management which uses machine learning models and deep learning techniques to predict system failures, optimize resource allocation, and enhance security postures. The aim of this paper is to present a complete analysis of AI-driven predictive models, highlighting anomaly detection, fault prediction, workload forecasting, and self-healing mechanisms.

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Published

29-08-2024

How to Cite

[1]
R. Chandra Thota, “AI-Augmented Predictive Analytics for Proactive Cloud Infrastructure Management”, J. Sci. Tech., vol. 5, no. 4, pp. 246–264, Aug. 2024, doi: 10.55662/JST.2024.5407.

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