Measuring Application Interference With System-Level Instrumentation

In the rapidly expanding cloud continuum, efficient resource management presents a critical challenge, particularly in multi-tenant environments where applications share resources. Resource contention, often caused by application interference, can degrade performance and reduce efficiency. Thus, accurately measuring the potential of an application to interfere with other co-located application on shared resources is beneficial for improving the overall resource utilization and system performance. This paper introduces an interference profiler that employs system-level instrumentation to monitor possible interferences of applications across CPU, disk I/O, network I/O, caches, and memory. Using eBPF, the profiler provides insight into the system and application performance while maintaining low overhead. In a preliminary evaluation, we evaluated the validity of the monitored metrics as indicators of application interference and incorporated them into a prototype interference-aware scheduling approach. The results demonstrate the relevance of the metrics collected and indicate that their incorporation into scheduling can enhance performance.