Meta's FBDetect system, detailed in this research paper, is a robust, in-production performance regression detection system. It identifies minuscule performance regressions (as small as 0.005%) across millions of servers and hundreds of services by monitoring hundreds of thousands of time series metrics. Key to FBDetect's success are advanced techniques for subroutine-level performance analysis, filtering false positives, deduplicating correlated regressions, and root cause analysis. The paper validates FBDetect's effectiveness through simulations and real-world production data, showcasing its superiority over existing methods and highlighting the significance of its seven years of successful operation.