Ruth H.

Responsibilities:

• 🇬🇧 Message Load Testing Between MQTT and Kafka Inside GitHub Actions In this task, I built a full end-to-end soak testing environment that simulates continuous, high-volume message flow between MQTT and Kafka — entirely inside GitHub Actions, without Kubernetes. I created a custom Docker image for Mosquitto with a Kafka Bridge, designed a CI workflow that publishes and consumes large message streams, and used simulator.py and junitify.py to analyze message loss, latency, and reliability. The result was a fully automated CI pipeline that validates system stability on every change.

• 🇬🇧 Audio Metrics Microservice for MinIO + Prometheus I developed a microservice called sound_metrics that periodically scans ultrasonic audio files stored in MinIO and computes key metrics such as: • Average RMS • Amplitude standard deviation • Microphone uptime The service uses Python, Librosa, and ffmpeg for audio processing, exposes a Prometheus metrics endpoint, and runs as part of the system’s Docker Compose environment.

• 🇬🇧 ML Research and Model for Plant Stress Detection For the third task, I researched and built a machine-learning model that detects plant stress based on ultrasonic recordings. I worked on: • Collecting and organizing the dataset • Extracting features using Librosa • Generating spectrograms for CNN models • Training models in TensorFlow/PyTorch • Evaluating and saving results The model was packaged into a CronJob-style service that runs periodically, performs predictions, and logs them into PostgreSQL. When the model detects a condition that requires attention, it sends an alert message to Kafka, where it is then consumed and displayed to the user.