The rapid advancement of hardware technology has resulted in software becoming the new bottleneck in I/O performance. In low-latency storage systems, performance failures are inevitable, even with state-of-the-art hardware. This paper investigates the impact of such performance failures on the software stack within low-latency hardware environments. We propose a novel approach that leverages predictive techniques to anticipate and mitigate the performance degradation caused by hardware failures. Our method demonstrates significant improvements, particularly at the 95th and 99th percentile, showing the potential for substantial optimization in real-world applications. Through detailed observation and analysis, we aim to provide both theoretical insights and practical solutions to enhance the robustness and reliability of system software performance in low-latency storage systems.