Over the past decade, while log processing, metrics, and traces have advanced significantly, alert systems have largely remained static, relying on simple, static thresholds that can often miss critical issues due to their inflexibility. Coralogix highlights the limitations of traditional alert systems, which often fail to account for dynamic system behavior and unexpected "unknown unknowns," leading to blind spots and inefficiencies. To address these challenges, Coralogix introduces Dynamic Alerts, a machine learning-driven feature that learns and adapts to the baseline behavior of systems to detect true abnormalities. This approach allows companies to receive actionable insights without being overwhelmed by false positives or alert fatigue, enhancing their ability to respond effectively to incidents in real-time.