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

Comparison of Learning Distribution