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Mitch Gusat

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AAAI Conference 2022 System Paper

CCA: An ML Pipeline for Cloud Anomaly Troubleshooting

  • Lili Georgieva
  • Ioana Giurgiu
  • Serge Monney
  • Haris Pozidis
  • Viviane Potocnik
  • Mitch Gusat

The Cloud Causality Analyzer (CCA) is an ML-based analytical pipeline to automate the tedious process of Root Cause Analysis (RCA) of Cloud IT events. The 3-stage pipeline is composed of 9 functional modules, including dimensionality reduction (feature engineering, selection and compression), embedded anomaly detection, and an ensemble of 3 custom explainability and causality models for Cloud Key Performance Indicators (KPI). Our challenge is: How to apply a reduced (sub)set of judiciously selected KPIs to detect Cloud performance anomalies, and their respective root causal culprits, all without compromising accuracy?

v2026.09.13