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Event tracing is an important tool for understanding the performance of parallel applications. As concurrency increases in leadership-class computing systems, the quantity of performance log data can overload the parallel file system, perturbing the application being observed. In this work we present a solution for event tracing at leadership scales. We enhance the I/O forwarding system software to aggregate and reorganize log data prior to writing to the storage system, significantly reducing the burden on the underlying file system for this type of traffic. Furthermore, we augment the I/O forwarding system with a write buffering capability to limit the impact of artificial perturbations from log data accesses on traced applications. To validate the approach, we modify the Vampir tracing toolset to take advantage of this new capability and show that the approach increases the maximum traced application size by a factor of …