{"title":"ImpAPTr","authors":"Hao Wang, Guoping Rong, Yangchen Xu, Yong You","doi":"10.1145/3324884.3415301","DOIUrl":null,"url":null,"abstract":"As a common IT infrastructure, APM (Application Performance Management) systems have been widely adopted to monitor call requests to an on-line service. Usually, each request may contain multi-dimensional attributes (e.g., City, ISP, Platform, etc.), which may become the reason for a certain anomaly regarding DSR (De-clining Success Rate) of service calls either solely or as a combination. Moreover, each attribute may also have multiple values (e.g., ISP could be T-Mobile, Vodafone, CMCC, etc.), rendering intricate root causes and huge challenges to identify the root causes. In this paper, we propose a prototype tool, ImpAPTr (Impact Analysis based on Pruning Tree), to identify the combination of dimensional attributes as the clues to dig out the root causes of anomalies regarding DSR of a service call in a timely manner. ImpAPTr has been evaluated in MeiTuan, one of the biggest on-line service providers. Performance regarding the accuracy outperforms several previous tools in the same field.","PeriodicalId":267160,"journal":{"name":"Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3324884.3415301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
As a common IT infrastructure, APM (Application Performance Management) systems have been widely adopted to monitor call requests to an on-line service. Usually, each request may contain multi-dimensional attributes (e.g., City, ISP, Platform, etc.), which may become the reason for a certain anomaly regarding DSR (De-clining Success Rate) of service calls either solely or as a combination. Moreover, each attribute may also have multiple values (e.g., ISP could be T-Mobile, Vodafone, CMCC, etc.), rendering intricate root causes and huge challenges to identify the root causes. In this paper, we propose a prototype tool, ImpAPTr (Impact Analysis based on Pruning Tree), to identify the combination of dimensional attributes as the clues to dig out the root causes of anomalies regarding DSR of a service call in a timely manner. ImpAPTr has been evaluated in MeiTuan, one of the biggest on-line service providers. Performance regarding the accuracy outperforms several previous tools in the same field.