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Performance Debugging for Distributed Systems of Black Boxes

机译:黑匣子分布式系统的性能调试

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摘要

Many interesting large-scale systems are distributed systems of multiple communicating components. Such systems can be very hard to debug, especially when they exhibit poor performance. The problem becomes much harder when systems are composed of "black-box" components: software from many different (perhaps competing) vendors, usually without source code available. Typical solutions-provider employees are not always skilled or experienced enough to debug these systems efficiently. Our goal is to design tools that enable modestly-skilled programmers (and experts, too) to isolate performance bottlenecks in distributed systems composed of black-box nodes. We approach this problem by obtaining message-level traces of system activity, as passively as possible and without any knowledge of node internals or message semantics. We have developed two very different algorithms for inferring the dominant causal paths through a distributed system from these traces. One uses timing information from RPC messages to infer inter-call causality; the other uses signal-processing techniques. Our algorithms can ascribe delay to specific nodes on specific causal paths. Unlike previous approaches to similar problems, our approach requires no modifications to applications, middleware, or messages.
机译:许多有趣的大型系统是具有多个通信组件的分布式系统。这样的系统可能很难调试,特别是当它们表现不佳时。当系统由“黑匣子”组件组成时,问题将变得更加棘手:来自许多不同(可能是竞争产品)供应商的软件,通常没有可用的源代码。典型的解决方案提供商的员工并不总是有足够的技能或经验来有效地调试这些系统。我们的目标是设计工具,使中等技能的程序员(以及专家)也可以隔离由黑盒节点组成的分布式系统中的性能瓶颈。通过尽可能被动地获取系统活动的消息级跟踪,而无需了解节点内部或消息语义,我们可以解决此问题。我们已经开发了两种截然不同的算法,可以从这些迹线推断出通过分布式系统的主要因果路径。一种是使用来自RPC消息的计时信息来推断呼叫间的因果关系;另一种是使用RPC消息来推断因果关系。另一种使用信号处理技术。我们的算法可以将延迟归因于特定因果路径上的特定节点。与以前解决类似问题的方法不同,我们的方法不需要修改应用程序,中间件或消息。

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