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Industrial Edge & Azure IoT Operations

A unified data plane for the Azure cloud

Bring shop floor data into the Microsoft Azure ecosystem with an open, edge-first architecture. Siemens Industrial Edge handles connectivity, data harmonization and contextualization, and local intelligence on the factory side.

Overview

Azure IoT Operations aggregates information across multiple edge devices and other data sources; and Azure's data and AI services make that information usable across the enterprise, in the form of advanced analytics, and AI use cases.

Together, Siemens Industrial Edge and Microsoft Azure provide scalable edge-to-cloud infrastructure for building a unified manufacturing data plane. This foundation supports hybrid use cases across the edge and cloud, including real-time production analytics, predictive maintenance, predictive quality, visual quality inspection, and closed-loop agentic and physical AI applications.

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Siemens Industrial Edge brings compute and connectivity directly onto the shop floor, where it connects to heterogeneous machines and controllers and runs local apps for industrial connectivity and real-time processing, managed centrally through Siemens’ edge management layer. In parallel, Azure IoT Operations—deployed on Azure Arc-enabled Kubernetes—provides the factory-level, standardized data and operations layer that models and routes industrial data consistently and securely from the site into Azure services. Together, this edge-to-cloud pairing reduces IT/OT integration friction by enabling continuous data flow from industrial assets to Azure IoT Operations, while allowing manufacturers to keep latency-sensitive workloads at the edge. The result is a clear, scalable path from sensor to decision, built on open standards and ready for multi-site rollouts.

Siemens Industrial Edge to Microsoft Azure

  1. Connect vendor agnostic shopfloor equipment to Industrial Edge via pre-configured connectors.
  2. Bridge factory and cloud through Azure IoT Operations on Arc-enabled Kubernetes
  3. Manage data, power AI use cases and run real-time analytics with Microsoft Fabric, Fabric RTI, and Power BI.
  4. Add industrial context with Fabric IQ, Foundry IQ, and Work IQ knowledge layer.
  5. Train and deploy AI models using Azure ML and Microsoft Foundry
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Detailed architecture

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Detailed Architecture

    Field level: Siemens Industrial Edge as the OT foundation

    On the shop floor, Siemens Industrial Edge connects directly to PLCs, drives, robots, and other automation equipment using protocols such as EtherNet/IP, Modbus TCP, and OPC UA and multiple other protocols covering the vast majority of the industrial installed base. A library of pre-configured OT and IT connectors removes most of the integration work that traditionally slows down digitalization projects.

    Local apps run alongside the connectors on the same Siemens Industrial Edge Device, including WinCC Unified for visualization, Virtual PLC and LiveTwin for control and executable digital twins, the AI Inference Server for on-device machine learning, and tools like Energy Manager and Performance Insight for operational KPIs. A Databus based on MQTT keeps these apps loosely coupled and easy to extend. The Industrial Information Hub (IIH) suite takes care of the data harmonization, pre-processing and contextualization, enabling the shopfloor data to be used in smart applications at the edge, the factory data center and the cloud.

    IIH can then connect to multiple northbound targets, including Azure IoT Operations, Azure IoT Hub (direct-to-cloud), Azure Event Grid (direct-to-cloud), Enterprise MQTT brokers, and cloud applications running on Azure such as Senseye, a cloud-based Predictive Maintenance solution. Senseye uses AI to forecast machine failures, helping businesses reduce downtime. Insights Hub, is a scalable IIoT platform for collecting, storing and analyzing industrial data. Senseye and Insights Hub are both available on the Azure Marketplace.

    Factory level: Azure IoT Operations as a key element of the adaptive factory

    At the factory level, Azure IoT Operations—running on Azure Arc-enabled Kubernetes—establishes a standardized industrial data plane that bridges OT and IT and provides a consistent, real-time data foundation.

    It ingests data from distributed edge environments through built-in connectors (e.g., OPC UA, MQTT, REST), applies asset modeling and schema definitions, and transforms raw signals into structured, contextualized data.

    An integrated MQTT broker acts as the core messaging backbone, enabling bi-directional communication and unified namespace patterns across systems. Dataflows define how data is processed, routed, and delivered to Microsoft Fabric.

    Built on Kubernetes with Akri-based connectors, schema registry, and asset registry, Azure IoT Operations provides a modular, scalable architecture with built-in buffering to ensure data continuity during disruptions.

    This creates a unified data backbone that enables closed-loop, adaptive operations —where data flows seamlessly from machines to enterprise systems, powering AI, analytics, and continuous optimization.

    IT and enterprise level: the Azure data and AI stack

    Once data reaches Azure, a layered set of services turns it into business value:

    • Data management and real-time analytics with Microsoft Fabric, Fabric Real-Time Intelligence, and Power BI
    • Contextual intelligence and knowledge layer with Fabric IQ, Foundry IQ, and Work IQ, which add industrial meaning to raw signals
    • AI training and data engineering with Azure Machine Learning and Microsoft Foundry, including model deployment back to the edge
    • Connectivity and messaging with Azure IoT Hub and Event Grid for secure, bidirectional communication
    • Cloud-based industrial workloads including Senseye Predictive Maintenance, Insights Hub, Mendix, and RapidMiner AI Cloud and Graph Studio.

    Scalable, production-grade infrastructure management across the stack

    The Siemens Industrial Edge Management application provides a unified operational layer to deploy apps, push updates, monitor device health, and manage AI models across all sites. Combined with Azure's native governance and identity tooling, this gives IT and OT teams a shared operating model without forcing either side to give up control of their domain. Azure Arc provides a single pane of glass for IT infrastructure management from the cloud to the factory.

    Values & benefits

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    Built for reality of industrial environments

    Siemens Industrial Edge connects to equipment from any vendor, enabling a production-ready architecture that works in brownfield environments without requiring costly replacement or redesign.

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    Operations that don’t stop when connectivity does

    Critical applications—control logic, visualization, and buffering—run locally. Production continues and operators stay in control, even during cloud or network disruptions.

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    A single semantic model from machine to enterprise

    Azure IoT Operations and the Fabric IQ / Foundry IQ / Work IQ layer establish a consistent data language across the stack—ensuring that what a signal means on the shop floor is the same in analytics and decision-making systems.

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    AI that moves from insight to action

    Models trained in Azure ML and Microsoft Foundry are deployed directly to Siemens Industrial Edge, enabling real-time inference at the source and closing the loop between analytics and operations.

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    From one line to a global system—by design

    The architecture scales from a single machine to a global fleet, combining Siemens Industrial Edge as the industrial operations platform across shop floors with Azure IoT Operations as the data and application layer across sites.

    Components

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    Siemens Industrial Edge (field level)

    Siemens Industrial Edge Devices running OT and IT connectors, local apps - WinCC Unified, Virtual PLC, LiveTwin, Mendix on Edge, Energy Manager, and Performance Insight, plus AI Inference Server and Industrial Information Hub.

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    Azure IoT Operations (factory level)

    It provides a factory data layer, normalizing and routing shop floor data via OPC UA, MQTT, and REST. It includes Dataflows, an MQTT Broker, connectors, buffering for resilience, and scalable integration with Azure analytics & AI.

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    Azure cloud services (IT and enterprise level)

    Microsoft Fabric, Fabric RTI, and Power BI for data and analytics; Fabric IQ, Foundry IQ, and Work IQ for contextualization; Azure ML and Microsoft Foundry for AI; Azure IoT Hub and Event Grid for connectivity.