Today, event logging is a widely accepted concept with a number of event formatting standards and event collection protocols. Event logs contain valuable information not only about system faults and performance issues, but also about security incidents. Unfortunately, since modern data centers and computer networks are known to produce large volumes of log data, the manual review of collected data is beyond human capabilities. For automating this task, a number of data mining algorithms and tools have been suggested in recent research papers. In this paper, we will describe the application of the LogCluster tool for mining event patterns and anomalous events from security and system logs.