AutoARTS: Taxonomy, Insights and Tools for Root Cause Labelling of Incidents in Microsoft Azure

AutoARTS: Taxonomy, Insights and Tools for Root Cause Labelling of Incidents in Microsoft Azure
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发表时间:
2023
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通讯作者:
Pradeep Dogga;Chetan Bansal;Richard Costleigh;Gopinath Jayagopal;Suman Nath;Xuchao Zhang
Pradeep Dogga;Chetan Bansal;Richard Costleigh;Gopinath Jayagopal;Suman Nath;Xuchao Zhang
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作者:
Pradeep Dogga;Chetan Bansal;Richard Costleigh;Gopinath Jayagopal;Suman Nath;Xuchao Zhang

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将事件事后分析与根本原因联系起来对于汇总分析至关重要,汇总分析可以揭示可能导致未来事件的常见问题领域、趋势、模式和风险。一种常见的做法是根据根原因标签的专门分类法,用单个根原因手动标记事后分析。然而,这种手动过程容易出错,单一的根本原因不足以捕获事件背后的所有促成因素,并且临时分类法不能反映根本原因的不同类别。在本文中,我们解决这个问题的三管齐下的方法。首先,我们对Microsoft Azure中450多个服务的2000多个事件进行了广泛的多年分析,以了解导致这些事件的所有因素。其次,在实证研究的基础上,提出了一种新的生产事故潜在影响因素的层次和综合分类法。最后,我们开发了一个自动化工具,可以帮助人类在标签过程中。我们提出了实证评估和用户研究,表明我们的方法的有效性。据我们所知,这是迄今为止对生产事故事后报告进行的最大和最全面的研究。我们还公开了我们的分类法。
Labelling incident postmortems with the root causes is essential for aggregate analysis, which can reveal common problem areas, trends, patterns, and risks that may cause future incidents. A common practice is to manually label postmortems with a single root cause based on an ad hoc taxonomy of root cause tags. However, this manual process is error-prone, a single root cause is inadequate to capture all contributing factors behind an incident, and ad hoc taxonomies do not reflect the diverse categories of root causes. In this paper, we address this problem with a three-pronged approach. First, we conduct an extensive multi-year analysis of over 2000 incidents from more than 450 services in Microsoft Azure to understand all the factors that contributed to the incidents. Second, based on the empirical study, we pro-pose a novel hierarchical and comprehensive taxonomy of potential contributing factors for production incidents. Lastly, we develop an automated tool that can assist humans in the labelling process. We present empirical evaluation and a user study that show the effectiveness of our approach. To the best of our knowledge, this is the largest and most comprehensive study of production incident postmortem reports yet. We also make our taxonomy publicly available.