Azure IoT Edge
Cloud intelligence deployed locally on IoT edge devices
Build the intelligent edge
Azure IoT Edge is a fully managed service built on Azure IoT Hub. Deploy your cloud workloads – artificial intelligence, Azure and third-party services, or your own business logic – to run on Internet of Things (IoT) edge devices via standard containers. By moving certain workloads to the edge of the network, your devices spend less time communicating with the cloud, react more quickly to local changes and operate reliably even in extended offline periods.
Certified IoT Edge hardware: Works with your Linux or Windows devices that support container engines
Runtime: Free and open-source under the MIT licence to give you more control and code flexibility
Modules: Docker-compatible containers from Azure services or Microsoft partners to run your business logic at the edge
Cloud interface: Remotely manage and deploy workloads from the cloud through Azure IoT Hub with zero-touch device provisioning
Offload AI and analytics workloads to the edge
Deploy models built and trained in the cloud and run them on-premises. For example, if you deploy a predictive model to a factory camera to test for quality control and an issue is detected, IoT Edge triggers an alert and processes the data locally or sends it to the cloud for further analysis.
Use existing developer skillsets and code in a language you know. IoT Edge code is consistent across the cloud and the edge, and it supports languages such as C, C#, Java, Node.js and Python.
Respond in near-real time
Having the lowest latency possible between the data and the decision is critical. Rather than process your data in the cloud, IoT Edge processes it on the device itself, with the option of using hardware architecture from Microsoft called Project Brainwave. It uses a field-programmable gate array (FPGA) to make real-time AI calculations, giving you the immediate insights you need to make critical business decisions.
Reduce IoT solution costs
Only a small fraction of IoT edge data acquired is meaningful post-analytics. Use services such as Azure Stream Analytics or cloud-trained machine learning models to process the data locally and send only what’s needed to the cloud for further analysis. This reduces the cost associated with sending all your data to the cloud while maintaining high data quality.
Operate offline or with intermittent connectivity
Operate your edge devices reliably and securely, even when they’re offline or they have intermittent connectivity to the cloud. Azure IoT Edge device management automatically syncs the latest state of your devices once they’ve reconnected to ensure seamless operability.
JulyOT 2021 - 31 days of learning and upskilling for everyone interested in the Internet of Things
It’s time for another round of #JulyOT! This themed month of content focuses on all things related to the development of IoT Solutions designed to demonstrate and teach you how to build projects with Azure Internet of things (IoT) services.
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IoT Edge security for your enterprise edge deployments
- Ensures that your devices have the right software and that only authorised edge devices can communicate with one another
- Integrates with Azure Defender for IoT to help provide end-to-end threat protection and security posture management
- Supports any hardware security module to provide strong authenticated connections for confidential computing
IoT Edge pricing
IoT Edge consists of the edge runtime, edge modules and a cloud interface via Azure IoT Hub. The IoT Edge runtime is open-source and free.See IoT Edge pricing
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Documentation, resources and learning tools
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IoT Edge updates, blogs and announcements
Frequently asked questions about Azure IoT Edge
IoT Edge has three components. IoT Edge modules are containers that run Azure services, third-party services or custom code. They are deployed to IoT Edge-enabled devices and execute locally on those devices. The IoT Edge runtime runs on each IoT Edge-enabled device and manages the modules deployed to each device. The cloud-based interface remotely monitors and manages IoT Edge-enabled devices.
IoT Edge also offers:
- Moby container management system
- High availability with Kubernetes
- Extended offline operation
- Zero-touch provisioning of edge devices
- Security manager with support for hardware-based root of trust
- Automatic Device Configuration Service for scaled deployment and configuration of edge devices
- Support for SDKs in C, C#, Node, Python and Java
- Tooling for module development, including coding, testing, debugging and deployment
- CI/CD pipeline using Azure DevOps
IoT Edge is among the most open edge platforms available today, and Microsoft is committed to using open-source technologies to deliver innovations at the edge. The IoT Edge runtime is open-sourced under MIT licence to give you more control and flexibility of the code. We support the Moby container management system, which extends the concepts of containerisation, isolation and management from the cloud to devices at the edge. We also support Kubernetes to manage your IoT Edge deployments; manage devices from multiple IoT hubs using a single Kubernetes interface.
IoT Edge supports Azure, third-party and custom logic running at the edge. To take advantage of edge capabilities, browse edge modules on the Azure Marketplace. They’re container-based and certified to work with IoT Edge for faster time to market. If you’re a software partner, learn how to publish IoT Edge modules.
IoT Edge supports Windows and Linux operating systems, and runs on devices with as little as 128 MB of memory. See the Azure Certified for IoT device catalogue to find third-party hardware certified based on core functionalities such as AI support, device management and security. If you’re a hardware partner, learn how to certify your edge hardware.
Microsoft has partnerships with DJI, Qualcomm, SAP and NVIDIA for IoT Edge services. Develop IoT Edge solutions to run on your high-end GPU-powered commercial drones with DJI. Run IoT Edge and AI services on the Snapdragon camera platform using the Vision AI developers kit with Qualcomm. Deploy essential business functions as edge modules with SAP. Get real-time video analytics at the edge by converting video feeds into sensor telemetry with NVIDIA.