基于服务的云平台应用程序监控分析系统  

Service-based Application Monitoring and Analysis System of Cloud Platform

作　　者：罗理机 唐华 周昕 张涛 LUO Li-Ji;TANG Hua;ZHOU Xin;ZHANG Tao(Information Technology Center,Hubei University of Technology,Wuhan 430068,China)

机构地区：[1]湖北工业大学信息技术中心,武汉430068

出　　处：《计算机系统应用》2022年第7期85-92,共8页Computer Systems & Applications

基　　金：湖北省教育厅人文社科基金(15Q065)。

摘　　要：针对云平台中对应用程序的性能监控方法存在全流程收集分析异常能力不足的问题,提出一种基于云平台服务组件的应用程序异常检测和瓶颈识别系统(AAD-PSC),可对多层架构云平台上的应用程序提供可自定义指标值的监控分析能力.系统首先在前端应用服务层收集云平台服务调用数据并与异常事件相关联;然后为应用程序适配定制化的异常检测方法,达到最优检测效果;最后查明由非工作负载变化引起的性能异常,并对其进行瓶颈识别.实验结果表明,监控系统可快速准确检测不同类别的异常事件并识别性能瓶颈,能够满足云平台下对应用程序的性能监控需求.To address the problem that the methods of cloud platforms to monitor application performance have a poor ability to collect and analyze anomalies in the whole process,this study proposes an application anomaly detection and bottleneck identification system based on cloud platform service components(AAD-PSC)that can provide monitoring and analysis characterized by customizable indicator values of applications on a cloud platform with multi-tier architecture.For this purpose,this system collects service invocation data at the front-end application service layer and correlates them with anomaly events.Then,customized anomaly detection methods are determined for the applications to achieve the optimal detection results.Finally,performance anomalies caused by non-workload changes are identified,and bottleneck identification is conducted.Experimental results show that the proposed monitoring system is able to quickly and accurately detect different types of anomaly events and identify corresponding performance bottlenecks and meets the needs of a cloud platform in application performance monitoring.

关 键 词：云平台 应用程序 服务组件 瓶颈识别 性能监控 大数据 

分 类 号：TP393.09[自动化与计算机技术—计算机应用技术]