A Reproducible Profiling Framework for a MQTT-to-Kafka Pipeline
| Vortragende(r) | Jonas Bruer | |
|---|---|---|
| Vortragstyp | Bachelorarbeit | |
| Betreuer(in) | Maximilian Hummel | |
| Termin | Fr 13. März 2026, 14:00 (Raum 010 (Gebäude 50.34)) | |
| Vortragssprache | Deutsch | |
| Vortragsmodus | in Präsenz | |
| Kurzfassung | Bridging MQTT-based IoT communication with Apache Kafka enables scalable data streaming but introduces additional processing stages that may become performance bottlenecks. Existing benchmarks mainly evaluate MQTT brokers in isolation or rely on black-box end-to-end measurements, offering limited insight into internal pipeline behavior.
This thesis presents a reproducible profiling framework for a MQTT-to-Kafka pipeline that combines benchmarking with white-box instrumentation of internal components. The framework models atomic Entry Level System Calls (ELSCs) and composes them into configurable workload classes, enabling automated and systematic performance experiments. The implementation is based on EMQX with integrated Kafka bridging and distributed tracing across protocol boundaries. Evaluation following a Goal-Question-Metric approach demonstrates that the framework supports reproducible experiments, preserves trace continuity across services, and enables identification of internal bottlenecks while maintaining controlled instrumentation overhead. | |