在基于容器的环境中监视事件的性能感知负载减少

Rolando Brondolin, M. Ferroni, M. Santambrogio
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引用次数: 3

摘要

运行时监控工具已经成为评估复杂系统和应用程序正确操作的基础。不幸的是,监视越精确(采样率、信息粒度等等),系统本身引入的开销就越高。在本文中,我们提出了一个新的负载减少框架,该框架支持在系统负载较重的情况下对监视代理进行运行时适应,利用启发式负载管理器来控制代理状态,并在运行时支持特定于领域的策略。我们在Sysdig上实现了所提出的方法,与以前的解决方案相比,平均控制误差提高了3.51倍(最多12.25倍)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance-aware load shedding for monitoring events in container based environments
Runtime monitoring tools have become fundamental to assess the correct operation of complex systems and applications. Unfortunately, the more precise is the monitoring (sampling rate, information granularity, and so on), the higher is the overhead introduced in the system itself. In this paper, we propose a new load shedding framework that enables runtime adaptation of monitoring agents under heavy system load, exploiting an heuristic Load Manager to control the agent status and a runtime support for domain-specific policies. We implemented the proposed methodology on Sysdig, with an average control error improvement of 3.51x (12.25x at most), w.r.t. previous solutions.
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