{"title":"基于服务的云平台应用监控分析","authors":"Yuecan Liu, Jiangang Sun, Yuzhu Chang, Qingfu Yang, Linwei Yang, Jing Li","doi":"10.1109/IAEAC54830.2022.9929714","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"113 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Service-based cloud platform application monitoring analysis\",\"authors\":\"Yuecan Liu, Jiangang Sun, Yuzhu Chang, Qingfu Yang, Linwei Yang, Jing Li\",\"doi\":\"10.1109/IAEAC54830.2022.9929714\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":349113,\"journal\":{\"name\":\"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )\",\"volume\":\"113 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAEAC54830.2022.9929714\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAEAC54830.2022.9929714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.