Open Source Summit North America 2025

In this presentation, Eoin will introduce a practical approach to Edge MLOps for microcontroller-based systems using the Zephyr RTOS. Edge MLOps unifies DevOps, ML model development, and edge deployment practices to streamline the entire AI lifecycle at the device level—from data collection and processing to model training, deployment, and continuous monitoring.

Attendees will learn how to implement version control for data and models, design automated CI/CD pipelines that handle real-world sensor data, and manage over-the-air (OTA) firmware updates on constrained Zephyr-based devices. We will explore best practices to ensure data integrity, model governance, and security throughout the pipeline, including techniques to mitigate model drift and bias.

Through a demonstration of an end-to-end IoT architecture, participants will see how edge devices can continuously collect new data, trigger remote training in the cloud, and deploy updated ML models back to the field. The talk will also highlight how Git action-based workflows enable seamless version transitions for on-device inference, showing how TFLite Micro or other open-source models —can be integrated platform-agnostic.