An Empirical Investigation of Incident Triage for Online Service SystemsSEIPIndustry Program
Online service systems have become increasingly popular. During operation of an online service system, incidents (unplanned interruptions or outages of the service) are inevitable. As an initial step of incident management, it is important to be able to automatically assign an incident report to a suitable team. We call this step incident triage, which can significantly affect the efficiency and accuracy of overall incident management. To better understand the incident-triage practice in industry, we perform an empirical study of incident triage on 20 real-world, large-scale online service systems in Microsoft. We find that incorrect assignment of incident reports occurs frequently and incurs unnecessary cost, especially for the incidents with high severity. For example, about 4.11% to 91.58% of incident reports are reassigned at least once and the average increment in incident-triage time caused by the reassignments is up to 10.16X. Considering the similarity between bug triage and incident triage, we then explore the applicability of typical bug-triage techniques to incident triage. The study results demonstrate that these bug-triage techniques are able to correctly assign incident reports to a certain extent, but still need to be improved, especially for the incident reports that are assigned incorrectly at the first time. We further discuss possible ways to improve the accuracy of incident-triage. To our best knowledge, we are the first to investigate incident triage in industrial practice. Our results are useful for both practitioners and researchers to develop methods and tools to improve the current incident-triage practice for online service systems.
Wed 29 MayDisplayed time zone: Eastern Time (US & Canada) change
14:00 - 15:30 | DevOps and LoggingSoftware Engineering in Practice / Technical Track / Papers at Mansfield / Sherbrooke Chair(s): Diomidis Spinellis Athens University of Economics and Business | ||
14:00 20mTalk | An Empirical Investigation of Incident Triage for Online Service SystemsSEIPIndustry Program Software Engineering in Practice Junjie Chen Peking University, Xiaoting He Microsoft, Qingwei Lin Microsoft Research, China, Yong Xu Microsoft, China, Hongyu Zhang The University of Newcastle, Dan Hao Peking University, Feng Gao Microsoft, Zhangwei Xu Microsoft, Yingnong Dang Microsoft Azure, Dongmei Zhang Microsoft Research, China | ||
14:20 20mTalk | Tools and Benchmarks for Automated Log ParsingSEIPIndustry Program Software Engineering in Practice Jieming Zhu Huawei Noah's Ark Lab, Shilin He Chinese University of Hong Kong, Jinyang Liu Sun Yat-Sen University, Pinjia He Computer Science and Engineering, The Chinese University of Hong Kong, Qi Xie Southwest Minzu University, Zibin Zheng School of Data and Computer Science, Sun Yat-sen University, Michael Lyu | ||
14:40 20mTalk | Mining Historical Test Logs to Predict Bugs and Localize Faults in the Test LogsTechnical TrackIndustry Program Technical Track | ||
15:00 20mTalk | DLFinder: Characterizing and Detecting Duplicate Logging Code SmellsTechnical TrackIndustry Program Technical Track Zhenhao Li Concordia University, Tse-Hsun (Peter) Chen Concordia University, Jinqiu Yang , Weiyi Shang Concordia University, Canada | ||
15:20 10mTalk | Discussion Period Papers |