Skip to content

ISSRE'20: Unsupervised Detection of Microservice Trace Anomalies through Service-Level Deep Bayesian Networks

Notifications You must be signed in to change notification settings

NetManAIOps/TraceAnomaly

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

48 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

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

image

About

ISSRE'20: Unsupervised Detection of Microservice Trace Anomalies through Service-Level Deep Bayesian Networks

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages