用于监控和测试云上web应用程序可伸缩性的框架

Martti Vasar, S. Srirama, M. Dumas
{"title":"用于监控和测试云上web应用程序可伸缩性的框架","authors":"Martti Vasar, S. Srirama, M. Dumas","doi":"10.1145/2361999.2362008","DOIUrl":null,"url":null,"abstract":"By allowing resources to be acquired on-demand and in variable amounts, cloud computing provides an appealing environment for deploying pilot projects and for performance testing of Web applications and services. However, setting up cloud environments for performance testing still requires a significant amount of manual effort. To aid performance engineers in this task, we developed a framework that integrates several common benchmarking and monitoring tools. The framework helps performance engineers to test applications under various configurations and loads. Furthermore, the framework supports dynamic server allocation based on incoming load using a response-time-aware heuristics. We validated the framework by deploying and stress-testing the MediaWiki application. An experimental evaluation was conducted aimed at comparing the response-time-aware heuristics against Amazon Auto-Scale.","PeriodicalId":116686,"journal":{"name":"Proceedings of the WICSA/ECSA 2012 Companion Volume","volume":"165 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Framework for monitoring and testing web application scalability on the cloud\",\"authors\":\"Martti Vasar, S. Srirama, M. Dumas\",\"doi\":\"10.1145/2361999.2362008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By allowing resources to be acquired on-demand and in variable amounts, cloud computing provides an appealing environment for deploying pilot projects and for performance testing of Web applications and services. However, setting up cloud environments for performance testing still requires a significant amount of manual effort. To aid performance engineers in this task, we developed a framework that integrates several common benchmarking and monitoring tools. The framework helps performance engineers to test applications under various configurations and loads. Furthermore, the framework supports dynamic server allocation based on incoming load using a response-time-aware heuristics. We validated the framework by deploying and stress-testing the MediaWiki application. An experimental evaluation was conducted aimed at comparing the response-time-aware heuristics against Amazon Auto-Scale.\",\"PeriodicalId\":116686,\"journal\":{\"name\":\"Proceedings of the WICSA/ECSA 2012 Companion Volume\",\"volume\":\"165 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the WICSA/ECSA 2012 Companion Volume\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2361999.2362008\",\"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 WICSA/ECSA 2012 Companion Volume","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2361999.2362008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26

摘要

通过允许按需以可变数量获取资源,云计算为部署试点项目以及Web应用程序和服务的性能测试提供了一个吸引人的环境。然而,为性能测试设置云环境仍然需要大量的手工工作。为了帮助性能工程师完成这项任务,我们开发了一个框架,该框架集成了几个常见的基准测试和监视工具。该框架帮助性能工程师在各种配置和负载下测试应用程序。此外,该框架还支持使用响应时间感知启发式方法根据传入负载进行动态服务器分配。我们通过部署和对MediaWiki应用程序进行压力测试来验证该框架。进行了一项旨在比较响应时间感知启发式和Amazon Auto-Scale的实验评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Framework for monitoring and testing web application scalability on the cloud
By allowing resources to be acquired on-demand and in variable amounts, cloud computing provides an appealing environment for deploying pilot projects and for performance testing of Web applications and services. However, setting up cloud environments for performance testing still requires a significant amount of manual effort. To aid performance engineers in this task, we developed a framework that integrates several common benchmarking and monitoring tools. The framework helps performance engineers to test applications under various configurations and loads. Furthermore, the framework supports dynamic server allocation based on incoming load using a response-time-aware heuristics. We validated the framework by deploying and stress-testing the MediaWiki application. An experimental evaluation was conducted aimed at comparing the response-time-aware heuristics against Amazon Auto-Scale.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信