In the context of modern software development, proactive monitoring is highlighted as a crucial advancement over traditional reactive monitoring, which primarily focuses on responding to system failures after they occur. Proactive monitoring leverages observability data and machine learning to predict and address potential issues before they result in significant system disruptions. This approach allows for the implementation of multiple alert levels, enabling teams to tackle issues of varying severity more effectively. By integrating machine learning, proactive monitoring can detect anomalous behavior that might not have been previously identified, providing a safety net that complements traditional alerts. Ultimately, this method supports operational and commercial success by offering deeper insights and reducing the likelihood of costly outages and service interruptions.