Trace-based Multi-Dimensional Root Cause Localization of Performance Issues in Microservice Systems
Modern microservice systems have become increasingly complicated due to the dynamic and complex interactions and runtime environment. It leads to the system vulnerable to performance issues caused by a variety of reasons, such as the runtime environments, communications, coordinations, or implementations of services. Traces record the detailed execution process of a request through the system and have been widely used in performance issues diagnosis in microservice systems. By identifying the execution processes and attribute value combinations that are common in anomalous traces but rare in normal traces, engineers may localize the root cause of a performance issue into a smaller scope. However, due to the complex structure of traces and the large number of attribute combinations, it is challenging to find the root cause from the huge search space. In this paper, we propose TraceContast, a trace-based multi-dimensional root cause localization approach. TraceContast uses a sequence representation to describe the complex structure of a trace with attributes of each span. Based on the representation, it combines contrast sequential pattern mining and spectrum analysis to localize multi-dimensional root causes efficiently. Experimental studies on a widely used microservice benchmark show that TraceContrast outperforms existing approaches in both multi-dimensional and instance-dimensional root cause localization with significant accuracy advantages. Moreover, TraceContrast is efficient and its efficiency can be further improved by parallel execution.
Thu 18 AprDisplayed time zone: Lisbon change
11:00 - 12:30 | Analysis and Debugging 2New Ideas and Emerging Results / Research Track at Luis de Freitas Branco Chair(s): Pedro Diniz | ||
11:00 15mTalk | Trace-based Multi-Dimensional Root Cause Localization of Performance Issues in Microservice Systems Research Track Chenxi Zhang Fudan University, Zhen Dong Fudan University, China, Xin Peng Fudan University, Bicheng Zhang Fudan University, Miao Chen Fudan University | ||
11:15 15mTalk | ReClues: Representing and indexing failures in parallel debugging with program variables Research Track Yi Song School of Computer Science, Wuhan University, Xihao Zhang School of Computer Science, Wuhan University, Xiaoyuan Xie School of Computer Science, Wuhan University, China, Quanming Liu School of Computer Science, Wuhan University, Ruizhi Gao Sonos Inc., Chenliang Xing School of Computer Science, Wuhan University | ||
11:30 15mTalk | PyAnalyzer: An Effective and Practical Approach for Dependency Extraction from Python Code Research Track Wuxia Jin Xi'an Jiaotong University, Shuo Xu Xi'an jiaotong university, Dawei Chen Xi'an Jiaotong University, Jiajun He Xi'an jiaotong university, Dinghong Zhong Xi'an jiaotong university, Ming Fan Xi'an Jiaotong University, Hongxu Chen Huawei Technologies Co., Ltd., Huijia Zhang Huawei Technologies Co Ltd, Ting Liu Xi'an Jiaotong University Media Attached | ||
11:45 15mTalk | Detecting Automatic Software Plagiarism via Token Sequence Normalization Research Track Timur Sağlam Karlsruhe Institute of Technology (KIT), Moritz Brödel Karlsruhe Institute of Technology (KIT), Larissa Schmid Karlsruhe Institute of Technology, Sebastian Hahner Karlsruhe Institute of Technology (KIT) DOI Pre-print | ||
12:00 15mTalk | NuzzleBug: Debugging Block-Based Programs in Scratch Research Track Pre-print | ||
12:15 7mTalk | Locating Buggy Segments in Quantum Program Debugging New Ideas and Emerging Results | ||
12:22 7mTalk | Beyond a Joke: Dead Code Elimination Can Delete Live Code New Ideas and Emerging Results Haoxin Tu Singapore Management University, Singapore, Lingxiao Jiang Singapore Management University, Debin Gao Singapore Management University, He Jiang Dalian University of Technology |