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Actionable and interpretable fault localization for recurring failures in online service systems

Zeyan Li, Nengwen Zhao, Mingjie Li, Xianglin Lu, Lixin Wang, Dongdong Chang, Xiaohui Nie, Li Cao, Wenchi Zhang, Kaixin Sui, Yanhua Wang, Xu Du, Guoqiang Duan, Dan Pei

2022Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering57 citationsDOIOpen Access PDF

Abstract

Fault localization is challenging in an online service system due to its monitoring data's large volume and variety and complex dependencies across/within its components (e.g., services or databases). Furthermore, engineers require fault localization solutions to be actionable and interpretable, which existing research approaches cannot satisfy. Therefore, the common industry practice is that, for a specific online service system, its experienced engineers focus on localization for recurring failures based on the knowledge accumulated about the system and historical failures. More specifically, 1) they can identify the underlying root causes and take mitigation actions when pinpointing a group of indicative metrics on the faulty component; 2) their diagnosis knowledge is roughly based on how one failure might affect the components in the whole system.

Topics & Concepts

Computer scienceBenchmark (surveying)Service (business)Variety (cybernetics)Rank (graph theory)Fault (geology)Artificial intelligenceMachine learningData miningInformation retrievalCombinatoricsGeographySeismologyGeologyGeodesyMathematicsEconomyEconomicsSoftware System Performance and ReliabilitySoftware Engineering ResearchAnomaly Detection Techniques and Applications