Proactive App Recommendations is a tool designed to help organizations manage the complexities of scaling operations by turning extensive telemetry data into actionable insights. As companies grow, they often face increased telemetry data from metrics, traces, logs, and frontend interactions, which can overwhelm teams trying to maintain service reliability and efficiency. This tool analyzes data from Application Performance Monitoring (APM), Real User Monitoring (RUM), Continuous Profiler, and Database Monitoring (DBM) to automatically identify performance and reliability issues, offering specific suggestions for fixes. It addresses backend inefficiencies by detecting patterns like sequential API calls that could be optimized, and it helps resolve frontend issues by identifying user frustration signals such as dead and rage clicks. Additionally, it provides code-level fixes for performance problems identified by the Continuous Profiler. Proactive App Recommendations streamlines the process of addressing telemetry data, minimizing the time required to implement necessary changes and enhancing the performance and reliability of services, all integrated within the Datadog platform at no additional cost to existing subscribers.