RUN (AAAI 2024)

Official code of the paper Root Cause Analysis In Microservice Using Neural Granger Causal Discovery .

Introduction

We propose a novel approach for root cause analysis using neural Granger causal discovery with contrastive learning.

Enhance the backbone encoder by integrating contextual information from time series
Leverage a time series forecasting model to conduct neural Granger causal discovery
In addition, we incorporate Pagerank with a personalization vector to efficiently recommend the top-k root causes

python main.py --root_path ./ --data_path data --root_cause root_cause --trigger_point trigger_point

Name		Name	Last commit message	Last commit date
Latest commit History 13 Commits
data_provider		data_provider
models		models
README.md		README.md
RUN.py		RUN.py
main.py		main.py
model.py		model.py
requirements.txt		requirements.txt