OpenAI engineers have described an investigation into rare infrastructure crashes that relied on large-scale core dump analysis. By treating crash data as epidemiological evidence, they were able to identify patterns that pointed to two distinct causes.
The analysis uncovered both a hardware fault and a software bug that had been present for 18 years. The age of the bug made it particularly difficult to isolate, as it had likely been hidden by the complexity of modern systems.
The work highlights how debugging large-scale AI infrastructure requires not just code inspection but also systematic analysis of system-generated data. The approach, which OpenAI calls core dump epidemiology, may be useful for other organizations running similarly complex systems.