The failure of FDL2 serves as a cautionary tale in the design of distributed systems. The reliance on perfect network conditions and synchronous consensus created a fragile architecture that could not withstand real-world volatility. By analyzing the "FDL2 failed" event, we identify that robustness in federated learning comes not from speed, but from the capacity to handle asynchronous, partial failures without corrupting the global state.