大数据运维中的自动化监控与故障排除  

Automated Monitoring and Fault Diagnosis in Big Data Operations and Maintenance

作　　者：梁景鹏 LIANG Jingpeng(Tianhe Computer Technology Co.,Ltd.,Tianjin 300457,China)

机构地区：[1]天津市天河计算机技术有限公司,天津300457

出　　处：《自动化与仪表》2025年第4期162-164,共3页Automation & Instrumentation

摘　　要：随着大数据技术的快速发展,大数据运维中的监控与故障排除面临着越来越多的挑战。该文旨在探讨如何利用自动化监控与故障排除技术应对这些挑战,首先介绍了当前大数据运维中监控与故障排除所面临的挑战。其次概述了监控系统及自动化监控技术的基本原理。然后,详细阐述了自动化故障排除方法,包括故障检测与诊断技术以及自动化故障处理策略。最后,展望了自动化监控与故障排除技术的未来发展趋势,并提出了面临的挑战与解决方案。该文通过系统的方法,阐述了大数据运维中自动化监控与故障排除的重要性,论证了其在提高运维效率和降低成本方面的价值,得出了对未来发展的展望与建议。With the rapid development of big data technologies,monitoring and fault diagnosis in big data operations and maintenance(O&M)are facing increasing challenges.This paper aims to explore how automated monitoring and fault diagnosis technologies can address these challenges.First,the paper introduces the challenges currently faced in monitoring and fault diagnosis in big data O&M.Then,it outlines the basic principles of monitoring systems and automated monitoring technologies.Next,the paper provides a detailed discussion of automated fault diagnosis methods,including fault detection and diagnosis technologies,as well as automated fault handling strategies.Finally,the paper looks at the future development trends of automated monitoring and fault diagnosis technologies,proposing challenges and solutions.Through a systematic approach,this paper emphasizes the importance of automated monitoring and fault diagnosis in big data O&M,demonstrates its value in improving O&M efficiency and reducing costs,and offers prospects and recommendations for future development.

关 键 词：大数据运维 自动化监控 故障排除 监控系统 技术发展 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]