TraceDiag: Adaptive, Interpretable, and Efficient Root Cause Analysis on Large-Scale Microservice Systems

Author:

Ding Ruomeng1,Zhang Chaoyun2,Wang Lu1,Xu Yong1,Ma Minghua2,Wu Xiaomin1,Zhang Meng3,Chen Qingjun3,Gao Xin3,Gao Xuedong3,Fan Hao3,Rajmohan Saravan4,Lin Qingwei2,Zhang Dongmei2

Affiliation:

1. Microsoft, Beijing, n.n.

2. Microsoft, Beijing, China

3. Microsoft 365, Suzhou, n.n.

4. Microsoft 365, Redmond, n.n.

Publisher

ACM

Reference64 articles.

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2. A Multiagent Reinforcement Learning algorithm to solve the Community Detection Problem;Alipour Mir Mohammad;Signal and Data Processing,2022

3. On-line fault detection and diagnosis obtained by implementing neural algorithms on a digital signal processor;Bernieri Andrea;IEEE Transactions on Instrumentation and Measurement,1996

4. Patrick Blöbaum Peter Götz Kailash Budhathoki Atalanti A. Mastakouri and Dominik Janzing. 2022. DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models. arXiv preprint arXiv:2206.06821. Patrick Blöbaum Peter Götz Kailash Budhathoki Atalanti A. Mastakouri and Dominik Janzing. 2022. DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models. arXiv preprint arXiv:2206.06821.

5. Graph-based root cause analysis for service-oriented and microservice architectures;Brandón Álvaro;Journal of Systems and Software,2020

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3. Network Analysis of Microservices: A Case Study on Alibaba Production Clusters;Companion of the 15th ACM/SPEC International Conference on Performance Engineering;2024-05-07

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