J. Kross, Felix Willnecker, Thomas Zwickl, H. Krcmar
{"title":"PET:连续性能评估工具","authors":"J. Kross, Felix Willnecker, Thomas Zwickl, H. Krcmar","doi":"10.1145/2945408.2945418","DOIUrl":null,"url":null,"abstract":"Performance measurements and simulations produce large amounts of data in a short period of time. Release cycles are getting shorter due to the DevOps movement and heavily rely on live data from production or test environments. In addition, performance simulations increasingly become accurate and close to exact predictions. Results from these simulations are reliable and can be compared with live data to detect deviations from expected behavior. In this work, we present a comprehensive tool that can process and analyze measurement as well as simulation data quickly utilizing big data technologies. Live measurement data and simulation results can be analyzed for detecting performance problems, deviations from expected behavior or to simply compare a performance model with real world applications.","PeriodicalId":240965,"journal":{"name":"Proceedings of the 2nd International Workshop on Quality-Aware DevOps","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"PET: continuous performance evaluation tool\",\"authors\":\"J. Kross, Felix Willnecker, Thomas Zwickl, H. Krcmar\",\"doi\":\"10.1145/2945408.2945418\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Performance measurements and simulations produce large amounts of data in a short period of time. Release cycles are getting shorter due to the DevOps movement and heavily rely on live data from production or test environments. In addition, performance simulations increasingly become accurate and close to exact predictions. Results from these simulations are reliable and can be compared with live data to detect deviations from expected behavior. In this work, we present a comprehensive tool that can process and analyze measurement as well as simulation data quickly utilizing big data technologies. Live measurement data and simulation results can be analyzed for detecting performance problems, deviations from expected behavior or to simply compare a performance model with real world applications.\",\"PeriodicalId\":240965,\"journal\":{\"name\":\"Proceedings of the 2nd International Workshop on Quality-Aware DevOps\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2nd International Workshop on Quality-Aware DevOps\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2945408.2945418\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Workshop on Quality-Aware DevOps","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2945408.2945418","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance measurements and simulations produce large amounts of data in a short period of time. Release cycles are getting shorter due to the DevOps movement and heavily rely on live data from production or test environments. In addition, performance simulations increasingly become accurate and close to exact predictions. Results from these simulations are reliable and can be compared with live data to detect deviations from expected behavior. In this work, we present a comprehensive tool that can process and analyze measurement as well as simulation data quickly utilizing big data technologies. Live measurement data and simulation results can be analyzed for detecting performance problems, deviations from expected behavior or to simply compare a performance model with real world applications.
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