Machine Learning Revolutionizing Server Management and Performance

Year : 2025 | Volume : 16 | Issue : 02 | Page : 36 44
    By

    Kazi Kutubuddin Sayyad Liyakat,

  1. Professor and Head, Department of Electronics and Telecommunication Engineering, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India

Abstract

The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion of a broader study on the subject. The application of machine learning to server systems is rapidly evolving, moving beyond simple monitoring and analysis to sophisticated predictive and optimization strategies. By analyzing vast streams of server telemetry data, containing CPU (central processing unit) consumption, memory ingesting, network traffics, and disk I/O (input/output), machine learning algorithms can recognize patterns and irregularities which will be impossible for human operators to identify in real-time. This capability enables a range of applications, including dynamic resource allocation, predictive maintenance, and automated security threat detection. The promise lies in creating a more responsive, efficient, and resilient server infrastructure capable of adapting to fluctuating demands and unforeseen challenges. By embracing the transformative prospective of machine learning, organizations can unlock new era of efficiency and intelligence at the very core of their information technology infrastructure. The future of data centers is undoubtedly intertwined with the evolution of intelligent servers powered by machine learning.

Keywords: Machine learning, servers, management, intelligent system, cloud computing

[This article belongs to Journal of Computer Technology & Applications ]

How to cite this article:
Kazi Kutubuddin Sayyad Liyakat. Machine Learning Revolutionizing Server Management and Performance. Journal of Computer Technology & Applications. 2025; 16(02):36-44.
How to cite this URL:
Kazi Kutubuddin Sayyad Liyakat. Machine Learning Revolutionizing Server Management and Performance. Journal of Computer Technology & Applications. 2025; 16(02):36-44. Available from: https://journals.stmjournals.com/jocta/article=2025/view=208028


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Regular Issue Subscription Review Article
Volume 16
Issue 02
Received 15/02/2025
Accepted 19/03/2025
Published 15/04/2025
Publication Time 59 Days
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