Azure IoT Edge

Azure IoT Edge deploys cloud intelligence locally onto IoT edge devices, letting organizations break up data silos and consolidate operational data at scale in the Azure Cloud while running workloads directly on the device itself. Remotely and securely deployed cloud-native workloads -- AI, Azure services, or an organization's own business logic -- run directly on IoT devices rather than depending on constant cloud connectivity.

This local-first design optimizes cloud spend and lets devices react faster to local changes, continuing to operate reliably even through extended offline periods. Development uses existing developer skillsets: IoT Edge code is consistent across cloud and edge, and supports C, C#, Java, Node.js and Python, so teams don't need to learn a new language just to target edge devices.

Azure Monitor integration lets teams remotely monitor IoT Edge devices at scale, with built-in metrics and curated visualizations giving visibility into the health and performance of edge applications directly in the Azure portal, combining on-demand device logs for best-in-class edge observability. Since only a small fraction of IoT edge data is meaningful post-analytics, services like Azure Stream Analytics or cloud-trained machine learning models can process data locally and send only what's needed to the cloud, reducing data transfer costs while maintaining insight quality. Full IoT Edge pricing is usage-based and not summarized on one page; Azure's general account signup includes free-tier credit that is not specific to IoT Edge itself.