Interference Monitoring for Colocated Workloads in Low-Entropy Computing Systems
Da Zhang, Haojun Xia, Xiaotong Wang, Yanchang Feng, Bibo Tu · 2025
Users' expectations of internet applications have extended beyond basic functionality to prioritize tail latency and minimal jitter, factors often impacted by competitive interference among colocated workloads in operating systems. In the context of low-entropy computing, it is essential to monitor thread-level interference among colocated processes in a real-time and software-defined manner. This paper introduces NoiseCatcher, an interference monitoring solution that provides nanosecond-level reporting with minimal overhead on mission-critical threads. By leveraging eBPF (Extended Berkeley Packet Filter) and in-kernel shared data structures, our approach efficiently captures essential system events without requiring costly context switches. Aggregated data is then transmitted to the Baseboard Management Controller (BMC) via the system bus for persistent storage, with access provided through open RESTful APIs for flexible querying. The solution is evaluated on a production server, with comparative analysis against the Linux kernel's OSNOISE tracer. Results indicate that our solution not only matches OSNOISE in functionality but also achieves nanosecond-level precision, minimized performance degradation.