Despite advances in the application of automated statistical and machine learning techniques to system log and trace data there will always be a need for human analysis of machine traces, because trace information on unstable systems may be incomplete, or incorrect. In addition, false positives from automated analysis will not likely disappear, and remediation measures and candidate fix tests will need to be evaluated. We present Zinsight, a visual and analytic tool that supports performance analysts and debugging, using large event traces to understand complex systems. This tool enables analysts to quickly create and manipulate high-level structural representations linked with statistical analysis derived from the underlying event trace data. The original raw trace is annotated with module names and a domain specific database is incorporated to relate software functions to module names. Navigable sequence context graph views present automatically extracted execution flow patterns fro...