智能运维中KPI异常检测的研究进展

Research progress of KPI anomaly detection in intelligent operation and maintenance

现有的网络监控和故障修复大多依赖规则系统或者人工处理,然而随着网络规模的不断增大和业务的多样化,这种方式难以满足要求。随着机器学习和深度学习等技术的快速发展,智能运维理论也取得了长足进步,利用人工智能技术提升网络运维智能化能力。KPI(key performance indicator)异常检测是智能运维的一项底层核心技术。针对KPI异常检测技术研究展开综述,对KPI数据和KPI异常进行了描述,并从单指标和多指标两个方面详细介绍了KPI异常检测技术的研究现状;分析了KPI检测的部署应用问题,讨论了未来的研究方向。

Existing network monitoring and fault repair mostly rely on rule systems or manual processing.However,the increase in network scale and the diversification of services make this approach difficult to deal with.With the rapid development of technology such as machine learning and deep learning,intelligent operation and maintenance theory has also made great progress,using artificial intelligence technology to enhance the intelligent ability of network operation and maintenance.KPI(key performance indicator)anomaly detection is an underlying core technology of intelligent operation and maintenance.A survey on the KPI anomaly detection technology was given.Firstly,the KPI data and KPI anomalies were described.Then the research progress of single-dimensional KPI and multi-dimensional KPI anomaly detection were introduced.Then,the deployment and application problems of KPI anomaly detection were analyzed.Finally,future research directions were discussed.