An approach to root cause determination in a complex systems based on monitoring and event data is disclosed. It includes a historical analysis of events with their probabilistic correlations. Applying information measures between the random variables which embody those events one can detect origins of problems and generate real-time recommendations for their locations in a hierarchical system. Estimation of system bottlenecks, as well as the risk of “black swan”-type events are also computed. The processes are based on a statistical processing of a virtual directed graph produced from historical events.