Azure-Samples/edge-aio-in-a-box
📦 Open Source ProjectAzure-Samples
A comprehensive deployment guide for running Azure IoT Operations and Edge AI workloads in a single environment.
The edge-aio-in-a-box repository serves as a blueprint for architects and engineers looking to bridge the gap between industrial IoT and modern AI. It provides the necessary configuration and deployment scripts to set up a robust edge environment using K3s. The project focuses on the Azure IoT Operations stack, allowing for seamless data ingestion, processing, and model inference at the edge. Key technical features include the integration of the Azure ML extension for model management, support for Small Language Models (SLMs) to run locally, and RAG (Retrieval-Augmented Generation) pipelines for industrial data analysis. By modularizing the deployment process, it allows teams to quickly iterate on custom AI models while maintaining connectivity to Azure cloud services for centralized management and orchestration.
💡Highlights
- ├─K3s-based edge orchestration
- ├─Azure IoT Operations integration
- └─Supports local SLM & RAG workflows
🎯For
- ├─IoT Engineers
- ├─Edge AI Developers
- └─Industrial Automation Architects