Automated processes and systems troubleshoot and optimize performance of applications running in distributed computing systems. An automated computer-implemented processes train an inference model for an application based on metrics associated with the application and a key performance indicator (“KPI”) of the application. When a run-time performance problem is detected in run-time KPI values of KPI, the trained inference model is applied to run-time metrics and run-time KPI values to identify relevant run-time metrics that can be used to identify the root cause of the performance problem. The root cause of the performance problem can be used to generate a recommendation for correcting the performance problem. An alert identifying the root cause of the performance problem and the recommendation for correcting the performance problem are displayed on an interface of a display, thereby enabling correction of the performance problem and optimization of the application.