P. Leitner, Christian Inzinger, W. Hummer, B. Satzger, S. Dustdar
{"title":"基于复杂事件处理范例的云服务的应用程序级性能监控","authors":"P. Leitner, Christian Inzinger, W. Hummer, B. Satzger, S. Dustdar","doi":"10.1109/SOCA.2012.6449437","DOIUrl":null,"url":null,"abstract":"Monitoring of applications deployed to Infrastructure-as-a-Service clouds is still an open problem. In this paper, we discuss an approach based on the complex event processing paradigm, which allows application developers to specify and monitor high-level application performance metrics. We use the case of a Web 2.0 sentiment analysis application to illustrate the limitations we currently experience with regard to cloud monitoring, and show how our approach allows for more expressive definitions of monitored metrics. Furthermore, we indicate how the higher-level metrics produced by our approach can be used to increase application elasticity in an existing cloud middleware.","PeriodicalId":298564,"journal":{"name":"2012 Fifth IEEE International Conference on Service-Oriented Computing and Applications (SOCA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"53","resultStr":"{\"title\":\"Application-level performance monitoring of cloud services based on the complex event processing paradigm\",\"authors\":\"P. Leitner, Christian Inzinger, W. Hummer, B. Satzger, S. Dustdar\",\"doi\":\"10.1109/SOCA.2012.6449437\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Monitoring of applications deployed to Infrastructure-as-a-Service clouds is still an open problem. In this paper, we discuss an approach based on the complex event processing paradigm, which allows application developers to specify and monitor high-level application performance metrics. We use the case of a Web 2.0 sentiment analysis application to illustrate the limitations we currently experience with regard to cloud monitoring, and show how our approach allows for more expressive definitions of monitored metrics. Furthermore, we indicate how the higher-level metrics produced by our approach can be used to increase application elasticity in an existing cloud middleware.\",\"PeriodicalId\":298564,\"journal\":{\"name\":\"2012 Fifth IEEE International Conference on Service-Oriented Computing and Applications (SOCA)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"53\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fifth IEEE International Conference on Service-Oriented Computing and Applications (SOCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SOCA.2012.6449437\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fifth IEEE International Conference on Service-Oriented Computing and Applications (SOCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOCA.2012.6449437","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application-level performance monitoring of cloud services based on the complex event processing paradigm
Monitoring of applications deployed to Infrastructure-as-a-Service clouds is still an open problem. In this paper, we discuss an approach based on the complex event processing paradigm, which allows application developers to specify and monitor high-level application performance metrics. We use the case of a Web 2.0 sentiment analysis application to illustrate the limitations we currently experience with regard to cloud monitoring, and show how our approach allows for more expressive definitions of monitored metrics. Furthermore, we indicate how the higher-level metrics produced by our approach can be used to increase application elasticity in an existing cloud middleware.