fse-baro 0.0.8

BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection

BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection

BARO is an end-to-end approach to perform anomaly detection and root cause analysis for microservices's failures. This repository contains the artifact for reproducing the main experimental results in our paper accepted to ESEC/FSE 2024, and reusing purposes.

Installation

Install from PyPI

pip install fse-baro

Or, build from source

git clone https://github.com/phamquiluan/baro.git && cd baro
pip install -e .

More details are in INSTALLATION.md.

How-to-use

from baro import BARO

m = BARO()

anomalies = m.detect_anomalies(data)
root_causes = m.rca(data, anomalies=anomalies)
print(root_causes)

Download Paper

TBD

Download Datasets

Our datasets are publicly available in Zenodo repository with the following information:

• Dataset DOI:
• Dataset URL: https://zenodo.org/records/11046533

Reproducibility

Check the Jupyter Notebook at tutorials/reproducibility.ipynb to reproduce the performance of BARO.

Citation

@inproceedings{pham2024baro,
  title={BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection},
  author={Luan Pham, Huong Ha, and Hongyu Zhang},
  booktitle={Proceedings of the ACM on Software Engineering, Vol 1},
  year={2024},
  organization={ACM}
}

Contact

[e-mail]