fse-baro 0.0.9

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

🕵️ BARO: Root Cause Analysis for Microservices

BARO is an end-to-end anomaly detection and root cause analysis approach for microservices's failures. This repository includes artifacts for reuse and reproduction of experimental results presented in our FSE'24 paper titled "BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection".

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 .

BARO has been tested on Linux and Windows, with different Python versions. More details are in INSTALL.md.

How-to-use

from baro.anomaly_detection import bocpd
from baro.root_cause_analysis import robust_scorer

anomalies = bocpd(data)  # the data and its visualization are presented in the Google Colab above.
root_causes = robust_scorer(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]