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At Most One Change Segmentation and Relative Correlation Ranking for Root Cause Analysis

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AmocRCA

AmocRCA is a highly effective and efficient approach to Root Cause Analysis (RCA) using metric data only that is based on a recent and promising approach for RCA named BARO. It leverages At Most One Change (AMOC) segmentation to make the scoring mechanism independent of anomaly detection, and employs a relative correlation ranking that enhances the scoring mechanism while reducing the need for a preselected set of metrics.

Prerequisites

  • unzip
  • wget
  • python

Installation

python -m venv ./venv
source ./venv/bin/activate
pip install -r requirements.txt

Datasets

./download_data.sh

Usage

python ./root_cause_analysis.py --rcr --lma --amoc

Reproduce RQ1 and RQ2

./anomaly_detection.sh

or

unzip evaluation_ad.zip

then

./root_cause_analysis.sh

Results can be found in evaluation_rca

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At Most One Change Segmentation and Relative Correlation Ranking for Root Cause Analysis

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