CCA: An ML Pipeline for Cloud Anomaly Troubleshooting

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?

Authors

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

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