Columbo: Low Level End-to-End System Traces through Modular Full-System Simulation

Jakob Görgen, Vaastav Anand, Hejing Li, Jialin Li, Antoine Kaufmann
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Abstract

Fully understanding performance is a growing challenge when building next-generation cloud systems. Often these systems build on next-generation hardware, and evaluation in realistic physical testbeds is out of reach. Even when physical testbeds are available, visibility into essential system aspects is a challenge in modern systems where system performance depends on often sub-$\mu s$ interactions between HW and SW components. Existing tools such as performance counters, logging, and distributed tracing provide aggregate or sampled information, but remain insufficient for understanding individual requests in-depth. In this paper, we explore a fundamentally different approach to enable in-depth understanding of cloud system behavior at the software and hardware level, with (almost) arbitrarily fine-grained visibility. Our proposal is to run cloud systems in detailed full-system simulations, configure the simulators to collect detailed events without affecting the system, and finally assemble these events into end-to-end system traces that can be analyzed by existing distributed tracing tools.
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科伦坡通过模块化全系统仿真进行低水平端到端系统跟踪
在构建下一代云系统时,充分了解性能是一个日益严峻的挑战。这些系统通常基于下一代硬件构建,在现实的物理测试平台上进行评估遥不可及。在现代系统中,系统性能往往取决于硬件和软件组件之间的交互,即使有物理测试平台,系统基本方面的可见性也是一个挑战。现有的工具,如性能计数器、日志记录和分布式跟踪可提供汇总或采样信息,但仍不足以深入了解单个请求。在本文中,我们将探索一种根本不同的方法,以便在软件和硬件层面深入了解云系统的行为,并实现(几乎)任意细粒度的可视性。我们的建议是在详细的全系统模拟中运行云系统,配置模拟器以在不影响系统的情况下收集详细事件,最后将这些事件组合成端到端系统跟踪,现有的分布式跟踪工具可对其进行分析。
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