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Abstract <p>Monitoring messages in system logs of servers of computing complexes is an actual challenge. Its solution can significantly increase the level of reliability of the MICC JINR by providing early warnings about possible emergency situations. This article proposes the concept of a LSTM neural model for automating the procedure for classifying system log messages, which is necessary for subsequent prediction of the occurrence of possible hardware and software failures of important components of the computing complex. Within the framework of the concept, programs for collecting and processing data, as well as an interface for their analysis, have been developed. Testing of the developed neural model LOGmon has shown the prospects of its application in the monitoring system of the MICC JINR.</p>

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Automated Analysis of System Logs of Serial Consoles of JINR MICC Servers

  • 期刊论文

  • 发表日期：

    2026年7月20日

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  • I. A. Kashunin,
  • G. A. Ososkoa,
  • A. V. Uzhinskiy,
  • E. I. Lysenko,
  • A. V. Baranov

摘要

Abstract

Monitoring messages in system logs of servers of computing complexes is an actual challenge. Its solution can significantly increase the level of reliability of the MICC JINR by providing early warnings about possible emergency situations. This article proposes the concept of a LSTM neural model for automating the procedure for classifying system log messages, which is necessary for subsequent prediction of the occurrence of possible hardware and software failures of important components of the computing complex. Within the framework of the concept, programs for collecting and processing data, as well as an interface for their analysis, have been developed. Testing of the developed neural model LOGmon has shown the prospects of its application in the monitoring system of the MICC JINR.