Microsoft's adaptive cloud approach brings cloud, edge, data, and AI together to help organizations turn operational technology (OT) data into intelligent action, without requiring everything to live in the cloud.
At the center of this approach are key technologies that connect physical operations to cloud-scale data, analytics, and AI:
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Key Purpose |
Offering |
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Direct-to-cloud device management + telemetry ingestion |
Azure IoT Hub |
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Industrial connectivity + edge data plane |
Azure IoT Operations |
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Unified analytics + real-time intelligence |
Microsoft Fabric |
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On-device AI inferencing runtime |
Microsoft Foundry |
Industry recognition
Microsoft named a Leader in the 2026 Gartner® Magic Quadrant™ for Global Industrial AIoT Platforms
Read the announcement
See it all come together
Before diving into each component, watch this end-to-end demo showing how Azure IoT Operations, Azure IoT Hub, Microsoft Fabric, and Foundry Local work as one stack across the edge-to-cloud lifecycle - Making industrial AI practical for real-world operations with adaptive cloud.
How these components work together
Azure IoT Operations and Azure IoT Hub collect real-time data from operational assets and send semantically-ready, modeled data to Microsoft Fabric, where it's contextualized with enterprise data for downstream analytics. Microsoft Foundry extends to the edge through Foundry Local, so the same tooling used to deploy and manage AI models in the cloud applies to edge use cases. All of it integrates into Azure Resource Manager, bringing OT devices, assets, and edge AI models into the same management and security paradigm as every other Azure-managed resource.
This blog walks through where to get started with each product capability:
1. Manage Cloud-Connected Devices and Telemetry with Azure IoT Hub
Azure IoT Hub is a fully managed cloud service that enables secure bidirectional communication, device-to-cloud telemetry ingestion, cloud-to-device command execution, per-device authentication, remote management and more.
Telemetry from IoT Hub can also be routed downstream into analytics platforms like Microsoft Fabric for visualization or AI modeling.
Recommended Usage:
Devices that utilize IoT Hub are distributed, stand-alone devices with fixed-functions. These devices typically do not require cloud-managed containerized workloads or cloud-managed proximal industrial protocol connectivity. Examples of appropriate device-to-cloud IoT Hub endpoint devices include water monitoring stations, vehicle telematics, distributed fluid level sensors, etc.
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Resources Current in-market services overview:
Try out our preview of new IoT Hub capabilities (integration with Azure Device Registry and Certificate Management)
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2. Connect Industrial Assets with Azure IoT Operations
Azure IoT Operations provides a unified data plane for the edge that runs on Azure Arc–enabled Kubernetes clusters and supports open industrial standards. It allows organizations to connect and capture equipment telemetry, normalize OT data locally, route hot-path signals to real-time analytics, securely manage layered industrial networks, and more.
Edge‑processed data can then be sent upstream to Microsoft Fabric for AI‑driven analysis.
Recommended Usage:
Azure IoT Operations is intended to be the data plane for an adaptive cloud deployment extending the management, data, and AI capabilities of the Microsoft cloud to an on-prem device. This device binds to these cloud planes providing a platform for local data processing and intermittent connectivity. The target for these devices range from a small-gateway-style PC to a full data center. Azure IoT Operations endpoints enable cloud-managed containerized workloads and cloud-managed proximal industrial protocol connectivity. Examples of appropriate adaptive cloud and Azure IoT Operations endpoints include, on-robot computers, industrial machine controllers, retail store sensor/vision processing, and top-of-factory site infrastructure for line of business applications.
3. Advanced Analytics with Microsoft Fabric
Microsoft Fabric delivers a unified, end‑to‑end analytics platform that transforms streaming OT telemetry into real‑time insights and live dashboards. Fabric Operations Agents monitor industrial signals to recommend targeted actions, while Fabric IQ provides a shared semantic foundation that enables AI agents to reason over enterprise data with business context. Together, Fabric turns live industrial data into AI‑powered operational intelligence.
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Resources |
4.Run AI Models On‑Device with Foundry Local
Foundry Local extends on‑device AI to Arc‑enabled Kubernetes edge clusters, providing a Microsoft‑validated inferencing layer for running AI models in industrial, disconnected or sovereign environments.
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Resources |
Customer Stories
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