We will go through a practical application of AI and machine learning for observability in Netdata, focusing on the utilization of anomaly detection for individual components. We will emphasize on ML’s role as an advisor rather than an alert mechanism, using multiple independent models to identify significant issues when different metrics indicate simultaneous anomalies. This method enhances the detection of unusual patterns, potentially predicting failures and identifying security breaches.
