Software Design Patterns for Latency Measurements with eBPF in SDN Environments

Abstract

This work proposes, implements, and evaluates a modular architecture based on software design patterns applied to latency measurement in Software-Defined Networks (SDN) using the Extended Berkeley Packet Filter (eBPF) and the Express Data Path (XDP). Unlike approaches that focus solely on measurement precision, this study examines how design patterns can structure observability systems in an extensible and maintainable way while preserving data-plane efficiency. The proposed architecture applies the Observer, Strategy, and Factory Method patterns to modularize the metric collection and analysis pipeline, allowing dynamic integration of policies and data sinks. The experimental environment was implemented with Mininet, Python agents, and eBPF/XDP programs, and was evaluated in terms of processing time, overhead, and evolution effort. The results show that the introduction of design patterns shows no clear evidence of measurable performance degradation, maintaining continuous measurements with a minimum of 5% overhead. The findings suggest that software engineering practices may be applied to the construction of eBPF-based monitoring and observability systems.