Core dump epidemiology: fixing an 18-year-old bug (openai.com)

OpenAI recently resolved a complex issue within its Rockset data infrastructure, which supports real-time analytics and search functionalities for ChatGPT. The problem stemmed from unusual crashes linked to a combination of two bugs: silent hardware corruption on an Azure host and an 18-year-old race condition in the GNU libunwind library. These crashes presented uniquely perplexing symptoms, where functions returned to invalid memory addresses, leading to significant system instability. The resolution involved applying an epidemiological approach to debug the situation—analyzing crash data across the entire system rather than focusing solely on isolated incidents. By automating the analysis of core dumps with a tailored script, OpenAI identified distinct crash populations, allowing them to pinpoint the hardware issue and alleviate misaligned-stack problems by removing the faulty host. This incident highlights the inherent challenges of managing low-level programming in C++, particularly regarding memory safety and reliability, while showcasing OpenAI's innovative troubleshooting methods that leverage data analysis to improve system robustness and prevent future occurrences.