Understanding Cache-Level Profiling of 5GC NFs

5G Core (5GC) network functions (NFs), including the Access and Mobility Management Function (AMF), Session Management Function (SMF), Network Repository Function (NRF), and User Plane Function (UPF), are increasingly deployed on commodity server hardware. As these functions run on general-purpose servers, their performance is significantly influenced by underlying micro-architectural behaviors such as Cache and memory-access behavior. Understanding this behavior is therefore important for performance analysis in practical deployments. Most existing studies examine open-source 5GC implementations, however, prominent 5G cores incorporate vendor-specific optimizations in scheduling, memory management, and packet processing that can affect how they use CPU and memory resources. As a result, observations from open-source systems do not generalize to production grade deployments. In this work, we present a measurement-driven characterization of key commercial 5GC network functions deployed as a virtualized network function. Using hardware performance counters collected via the Linux perf, we analyze the IPC and cache-related behavior of AMF, SMF, NRF, and UPF under two operating conditions: idle operation without active user equipment and live traffic generated by UEs. Our analysis reveals micro-architectural characteristics across control-plane and user-plane functions and shows how traffic conditions redistribute execution and memory-system pressure across the 5GC. Overall, this study demonstrates that hardware performance counter–based profiling provides a practical and non-intrusive means to characterize commercial 5GC network functions under realistic deployment conditions.