AI and Automation in Capacity Planning: Predicting and Managing Cloud Resource Demands

This article examines the transformative impact of Artificial Intelligence and automation on cloud capacity planning. It delves into how AI-driven systems revolutionize resource allocation, enabling organizations to optimize their infrastructure through predictive analytics and dynamic scaling. The article explores various aspects including machine learning models, automated scaling mechanisms, implementation challenges, and business benefits. By analyzing the evolution from traditional methods to AI-powered solutions, it demonstrates how organizations can achieve enhanced resource utilization, improved performance reliability, and significant cost optimization. The integration of edge computing and advanced AI capabilities emerges as crucial factors in shaping the future of cloud resource management, offering insights into upcoming trends and innovations in the field.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-03-09
DOI
https://doi.org/10.32628/cseit25112420
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
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article

AI and Automation in Capacity Planning: Predicting and Managing Cloud Resource Demands

Vineela Reddy Nadagouda
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Cloud Computing and Resource Management
article

AI and Automation in Capacity Planning: Predicting and Managing Cloud Resource Demands

Vineela Reddy Nadagouda
article en

Abstract

This article examines the transformative impact of Artificial Intelligence and automation on cloud capacity planning. It delves into how AI-driven systems revolutionize resource allocation, enabling organizations to optimize their infrastructure through predictive analytics and dynamic scaling. The article explores various aspects including machine learning models, automated scaling mechanisms, implementation challenges, and business benefits. By analyzing the evolution from traditional methods to AI-powered solutions, it demonstrates how organizations can achieve enhanced resource utilization, improved performance reliability, and significant cost optimization. The integration of edge computing and advanced AI capabilities emerges as crucial factors in shaping the future of cloud resource management, offering insights into upcoming trends and innovations in the field.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(2)
Quality and Reliability (Greece) (GR)
Openalex Percentile: Top 95%
Cloud Computing and Resource Management
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AI and Automation in Capacity Planning: Predicting and Managing Cloud Resource Demands — Vineela Reddy Nadagouda · International Journal of Scientific Research in Computer Science Engineering and Information Technology (2025) | TGRS Research Map | TGRS