NetManAIOps / Traceanomaly
ISSRE'20: Unsupervised Detection of Microservice Trace Anomalies through Service-Level Deep Bayesian Networks
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Programming Languages
python
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TraceAnomaly
Detecting anomalous traces of microservice system.
Paper
Ping Liu, Haowen Xu, Qianyu Ouyang, Rui Jiao, Zhekang Chen, Shenglin Zhang, Jiahai Yang, Linlin Mo, Jice Zeng, Wenman Xue, Dan Pei. Unsupervised Detection of Microservice Trace Anomalies through Service-Level Deep Bayesian Networks". 31th International Symposium on Software Reliability Engineering (ISSRE). IEEE, 2020
paper download（论文下载）：https://netman.aiops.org/wp-content/uploads/2020/09/%E5%88%98%E5%B9%B3issre.pdf
Dependencies
Python == 3.6
pip install -r requirements.txt
Docker Image
TraceAnomaly can be run directly in the Docker image: silence1990/docker_for_traceanomaly:latest
docker pull silence1990/docker_for_traceanomaly:latest
Dataset
Training set: train_ticket/train.zip
Test normal traces: train_ticket/test_normal.zip
Test anomalous traces: train_ticket/test_abnormal.zip
Usage
./run.sh
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