Microsoft’s adaptive cloud approach enables organizations to turn operational technology (OT) data into intelligent actions, autonomously, without requiring everything to live in the cloud by unifying cloud-to-edge management plane, data plane, and intelligence platform.
At the center of this approach are key foundational technologies:
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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 |
Foundry Local |
Microsoft Azure IoT Gartner winner: Microsoft named a Leader in the 2025 Gartner® Magic Quadrant™ for Global Industrial IoT Platforms
This blog walks through where to get started with each:
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.
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Resources
Latest Announcements & Blogs
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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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Get Started |
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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Get Started |
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