Root Cause Analysis of Failures in Microservices through Causal Discovery
Root Cause Analysis of Failures in Microservices through Causal Discovery
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发表时间：
2022
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通讯作者：
Azam Ikram;Sarthak Chakraborty;Subrata Mitra;S. Saini;S. Bagchi;Murat Kocaoglu
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作者：
Azam Ikram;Sarthak Chakraborty;Subrata Mitra;S. Saini;S. Bagchi;Murat Kocaoglu
大多数云应用程序使用大量较小的子组件（称为微服务），这些子组件以复杂的图形形式相互交互，为用户提供整体功能。虽然微服务架构的模块化有利于快速软件开发，但在故障情况下快速维护和调试这样的系统是具有挑战性的。我们提出了一种可扩展的算法，用于快速检测复杂微服务架构中故障的根本原因。我们新颖的分层和本地化学习方法背后的关键思想是：（1）将失败视为对根本原因的干预，以快速检测它，（2）只学习因果图中与根本原因相关的部分，从而避免大量昂贵的条件独立性测试，（3）分层探索图。所提出的技术是高度可扩展的，并产生有用的见解的根本原因，而使用传统的技术变得不可行，由于高计算时间。我们的解决方案与应用无关，仅依赖于收集的数据进行诊断。为了进行评估，我们将所提出的解决方案与PC算法的修改版本和最先进的根本原因分析进行了比较。结果表明，在top-k召回相当大的改善，同时显着减少了执行时间。
Most cloud applications use a large number of smaller sub-components (called mi-croservices) that interact with each other in the form of a complex graph to provide the overall functionality to the user. While the modularity of the microservice architecture is beneficial for rapid software development, maintaining and debugging such a system quickly in cases of failure is challenging. We propose a scalable algorithm for rapidly detecting the root cause of failures in complex microservice architectures. The key ideas behind our novel hierarchical and localized learning approach are: (1) to treat the failure as an intervention on the root cause to quickly detect it, (2) only learn the portion of the causal graph related to the root cause, thus avoiding a large number of costly conditional independence tests, and (3) hierarchically explore the graph. The proposed technique is highly scalable and produces useful insights about the root cause, while the use of traditional techniques becomes infeasible due to high computation time. Our solution is application agnostic and relies only on the data collected for diagnosis. For the evaluation, we compare the proposed solution with a modified version of the PC algorithm and the state-of-the-art for root cause analysis. The results show a considerable improvement in top-k recall while significantly reducing the execution time.