Logz.io is enhancing its open-source observability platform by introducing Anomaly Detection, a feature that leverages machine learning and artificial intelligence to analyze consolidated observability data for identifying performance issues before they affect customer experience. This new capability allows organizations to move beyond traditional monitoring, which typically involves setting static thresholds, by enabling a predictive approach that models historical telemetry data to uncover unknown anomalies. Anomaly Detection provides automated alerts and visualizations, helping reduce the time needed to address and investigate critical alerts, and it signifies a shift towards modern observability practices aimed at managing the vast amounts of data generated by cloud environments. Initially available for Log Management customers, the feature will extend to include metrics, traces, and security events, transforming how DevOps teams address issues in cloud-native applications.