» Xin Peng

Xin Peng

Professor of the School of Computer Science, Fudan University, China

Biography

Xin Peng received the bachelor’s and PhD degrees in computer science from Fudan University, in 2001 and 2006, respectively. He is a professor of the School of Computer Science, Fudan University, China. His research interests include data-driven intelligent software development, cloud-native software and AIOps, software engineering for AI and cyber-physical-social Systems. His work won the ICSM 2011 Best Paper Award, the ACM SIGSOFT Distinguished Paper Award at ASE 2018/2021, the IEEE TCSE Distinguished Paper Awards at ICSME 2018/2019/2020, and the IEEE Transactions on Software Engineering 2018 Best Paper Award. He was a steering committee member of International Conference on Software Maintenance and Evolution (ICSME) during 2017-2020. Now he is a co-editor of Journal of Software: Evolution and Process (JSEP), an editorial board member of ACM Transactions on Software Engineering and Methodology (TOSEM), Empirical Software Engineering (EMSE), and Chinese Journal of Software.

About the Talk

Large-Scale Trace Analysis for Microservice Anomaly Detection and Root Cause Localization

Abstract

Distributed tracing traces requests as they flow between services. It has been widely accepted and practiced in industry as an important means to achieve observability in microservice architecture for various purposes such as anomaly detection and root cause localization. However, trace analysis in an industrial microservice systems is often challenging due to the huge number of traces produced by the system and the difficulties in combining traces with other types of operation data such as logs and metrics. In this talk, I will first analyze the background and describe the industrial practice of distributed tracing and trace analysis. Then I will introduce our explorations on large-scale trace analysis for microservice anomaly detection and root cause localization.

All session by Xin Peng

Large-Scale Trace Analysis for Microservice Anomaly Detection and Root Cause Localization

10:30 - 11:15

Online