Online detection of multi-component interactions in production systems

We present an online, scalable method for inferring the interactions among the components of large production systems. We validate our approach on more than 1.3 billion lines of log files from eight unmodified production systems, showing that our approach efficiently identifies important relationships among components, handles very large systems with many simultaneous signals in real time, and produces information that is useful to system administrators.