DATA CENTRE MONITORING MODEL UTILIZING ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND ANOMALY DETECTION ALGORITHMS

Authors

  • Roberts Volkovičs PhD candidate, Vidzeme University of Applied Sciences (LV)

DOI:

https://doi.org/10.17770/etr2025vol2.8565

Keywords:

Data Centre, Monitoring, Tools and Techniques, Artificial Intelligence, Machine Learning, Anomaly Detection, Algorithms, Model

Abstract

In this article the review is created of architectures of popular data centre monitoring tools and corresponding information processing techniques are summarised. Pros and cons analysis of the monitoring tools is done and novel approach is offered by utilizing Artificial Intelligence (AI), Machine Learning (ML) and Anomaly Detection (AD) algorithms to achieve research goals and prove hypothesis that data centre level monitoring model could be built using combined AI, ML and AD techniques. Oracle performance metric data are collected to perform the information analysis from such angles the most modern enterprise monitoring tools do not provide yet.
Supporting Agencies
This research was funded by the European Commission, Research Executive Agency grant number 101079206, “Twinning in Environmental Data and Dynamical Systems Modelling for Latvia” (TED4LAT).

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Published

08.06.2025

How to Cite

[1]
R. Volkovičs, “DATA CENTRE MONITORING MODEL UTILIZING ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND ANOMALY DETECTION ALGORITHMS”, ETR, vol. 2, pp. 375–382, Jun. 2025, doi: 10.17770/etr2025vol2.8565.