Generic and Robust Root Cause Localization for Multi-Dimensional Data in Online Service Systems
Tsinghua University（清华大学）；Beijing National Research Center for Information Science and Technology (BNRist)（北京国家信息科学与技术研究中心（BNRist））；Tianjin University（天津大学）；Nankai University（南开大学）；Bizseer（必示科技）；China Construction Bank（中国建设银行）
Localizing root causes for multi-dimensional data is critical to ensure online service systems' reliability. When a fault occurs, only the measure values within specific attribute combinations are abnormal. Such attribute combinations are substantial clues to the underlying root causes and thus are called root causes of multidimensional data. This paper proposes a generic and robust root cause localization approach for multi-dimensional data, PSqueeze. We propose a generic property of root cause for multi-dimensional data, generalized ripple effect (GRE). Based on it, we propose a novel probabilistic cluster method and a robust heuristic search method. Moreover, we identify the importance of determining external root causes and propose an effective method for the first time in literature. Our experiments on two real-world datasets with 5400 faults show that the F1-score of PSqueeze outperforms baselines by 32.89%, while the localization time is around 10 seconds across all cases. The F1-score in determining external root causes of PSqueeze achieves 0.90. Furthermore, case studies in several production systems demonstrate that PSqueeze is helpful to fault diagnosis in the real world.
LongRCA Bench: Root-Cause Localization in Long-Horizon Agent Trajectories
Computer Network Information Center, Chinese Academy of Sciences（中国科学院计算机网络信息中心）；Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences（中国科学院大学杭州高等研究院）；Chongqing University（重庆大学）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；Singapore Management University（新加坡管理大学）；Tongyi Lab, Alibaba Group（阿里巴巴集团通义实验室）；Tsinghua University（清华大学）
eIRWR: Enhanced Iterative Random Walk with Restart for Scalable Root Cause Analysis in Microservices
Science and Technology Facilities Council（科学技术设施委员会）；RAL, Didcot, OX11 0QX, UK（RAL，迪德科特，OX11 0QX，英国）；Department of Engineering Science（工程科学系）；University of Oxford（牛津大学）
