E2EProf:企业系统的自动化端到端性能管理

S. Agarwala, Fernando Alegre, Karsten Schwan, Jegannathan Mehalingham
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引用次数: 77

摘要

由于Web服务、多层体系结构和网格计算的普遍使用,分布式系统正变得越来越复杂,其中动态组件集跨分布式和异构计算基础设施相互交互。因此,为了使这些应用程序能够可预测地并有效地向最终用户交付服务,理解和控制它们的运行时行为是至关重要的。例如,在数据中心环境中,理解某些IT子系统的端到端动态行为(从发出请求到生成响应并最终接收响应)是改进应用程序响应、提供所需的性能级别或满足服务级别协议(sla)的关键先决条件。E2EProf工具包支持对复杂企业应用程序的端到端程序行为进行高效且非侵入性的捕获和分析。E2EProf允许企业在出现性能问题时识别和分析性能问题——在线,尽可能快地采取纠正措施,并在用户请求当前采取的路径上采取必要的任何地方——端到端,并且不需要对应用程序进行检测——非侵入性。在线分析利用了一种称为路径映射的新颖信号分析算法,该算法动态检测客户机请求通过应用程序和后端服务器所采取的因果路径,并用端到端延迟以及不同路径组件对这些延迟的贡献来注释这些路径。因此,使用pathmap,可以动态地识别所选服务器或服务中存在的瓶颈,并检测指示潜在问题或过载的异常或不寻常的性能行为。Pathmap和E2EProf工具包成功地在ruby的类似ebay的多层Web应用程序和我们的行业合作伙伴Delta Air Lines的一个数据中心中检测到因果请求路径和相关的性能瓶颈。
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E2EProf: Automated End-to-End Performance Management for Enterprise Systems
Distributed systems are becoming increasingly complex, caused by the prevalent use of Web services, multi-tier architectures, and grid computing, where dynamic sets of components interact with each other across distributed and heterogeneous computing infrastructures. For these applications to be able to predictably and efficiently deliver services to end users, it is therefore, critical to understand and control their runtime behavior. In a datacenter environment, for instance, understanding the end-to-end dynamic behavior of certain IT subsystems, from the time requests are made to when responses are generated and finally, received, is a key prerequisite for improving application response, to provide required levels of performance, or to meet service level agreements (SLAs). The E2EProf toolkit enables the efficient and nonintrusive capture and analysis of end-to-end program behavior for complex enterprise applications. E2EProf permits an enterprise to recognize and analyze performance problems when they occur - online, to take corrective actions as soon as possible and wherever necessary along the paths currently taken by user requests - end-to-end, and to do so without the need to instrument applications - nonintrusively. Online analysis exploits a novel signal analysis algorithm, termed pathmap, which dynamically detects the causal paths taken by client requests through application and backend servers and annotates these paths with end-to-end latencies and with the contributions to these latencies from different path components. Thus, with pathmap, it is possible to dynamically identify the bottlenecks present in selected servers or services and to detect the abnormal or unusual performance behaviors indicative of potential problems or overloads. Pathmap and the E2EProf toolkit successfully detect causal request paths and associated performance bottlenecks in the RUBiS ebay-like multi-tier Web application and in one of the datacenter of our industry partner, Delta Air Lines.
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