基于服务的云平台应用监控分析

Yuecan Liu, Jiangang Sun, Yuzhu Chang, Qingfu Yang, Linwei Yang, Jing Li
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引用次数: 0

摘要

针对云平台应用性能监控方法在整个过程中异常采集和分析能力不足的问题,提出了一种基于云平台的方法。面向服务组件的应用异常检测和瓶颈识别系统,为多层云平台上的应用提供可定制的指标,价值监控和分析能力。系统首先采集前端应用服务层的云平台服务调用数据,并将其与异常事件关联;配置定制化异常检测方法,实现最优检测效果;最后,确定由非工作负载变化引起的性能异常,并确定瓶颈。实验结果表明,该监控系统能够快速准确地检测出不同类型的异常事件,识别出性能瓶颈,能够满足云平台下应用的性能需求。监控需求的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Service-based cloud platform application monitoring analysis
Aiming at the problem of insufficient ability to collect and analyze exceptions in the whole process of application performance monitoring methods in cloud platforms, a cloud platform-based method is proposed. Application Anomaly Detection and Bottleneck Identification System for Service Components, which provides customizable metrics for applications on multi-tier cloud platforms Value monitoring and analysis capabilities. The system first collects cloud platform service call data at the front-end application service layer and associates it with abnormal events;A customized anomaly detection method is configured to achieve the optimal detection effect; finally, performance anomalies caused by non-workload changes are identified and bottlenecks are identified. The experimental results show that the monitoring system can quickly and accurately detect different types of abnormal events and identify performance bottlenecks, which can meet the performance requirements of applications under the cloud platform. Ability to monitor demand.
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