Freshness review

Author: PatAltimore

articles/iot-edge/about-iot-edge.md

@@ -1,20 +1,25 @@
 ---
 title: What is Azure IoT Edge
-description: Overview of the Azure IoT Edge service and its components. Learn how to deploy, run, and monitor containerized Linux workloads at the edge.
+description: Learn how Azure IoT Edge enables you to deploy, run, and monitor containerized Linux workloads at the edge for better business insights and offline decision-making.
 author: PatAltimore
 ms.service: azure-iot-edge
 services: iot-edge
 ms.topic: overview
-ms.date: 06/12/2024
+ms.date: 03/20/2025
 ms.author: patricka
-ms.custom: mvc, linux-related-content
+ms.custom:
+  - mvc, linux-related-content
+  - ai-gen-docs-bap
+  - ai-gen-description
+  - ai-seo-date:03/20/2025
+#customer intent: As a developer, I want to know how to create and deploy custom IoT Edge modules so that I can run my business logic on edge devices.
 ---
 
 # What is Azure IoT Edge
 
 [!INCLUDE [iot-edge-version-all-supported](includes/iot-edge-version-all-supported.md)]
 
-Azure IoT Edge is a device-focused runtime that enables you to deploy, run, and monitor containerized Linux workloads.
+Azure IoT Edge is a device-focused runtime that enables you to deploy, run, and monitor containerized Linux workloads, bringing analytics closer to your devices for faster insights and offline decision-making.
 
 Analytics drives business value in IoT solutions, but not all analytics need to be in the cloud. Azure IoT Edge helps you bring the analytical power of the cloud closer to your devices to drive better business insights and enable offline decision making. For example, you can run anomaly detection workloads at the edge to respond as quickly as possible to emergencies happening on a production line. If you want to reduce bandwidth costs and avoid transferring terabytes of raw data, you can clean and aggregate the data locally then only send the insights to the cloud for analysis.
 
@@ -35,7 +40,7 @@ IoT Edge modules are units of execution, implemented as Docker-compatible contai
 
 ### Artificial intelligence at the edge
 
-Azure IoT Edge allows you to deploy complex event processing, machine learning, image recognition, and other high value AI without writing it in-house. Azure services like Azure Stream Analytics and Azure Machine Learning can all be run on-premises via Azure IoT Edge. You're not limited to Azure services, though. Anyone is able to create AI modules for your own use.
+Azure IoT Edge allows you to deploy advanced AI workloads like machine learning, image recognition, and complex event processing directly at the edge—without the need for in-house development. Azure services like Azure Stream Analytics and Azure Machine Learning can all be run on-premises via Azure IoT Edge. You're not limited to Azure services, though. Anyone is able to create AI modules for your own use.
 
 ### Bring your own code
 
@@ -67,11 +72,11 @@ Azure IoT Edge integrates seamlessly with [Azure IoT Central](../iot-central/ind
 * Send a workload to a set of devices.
 * Monitor workloads running on devices in the field.
 
-:::image type="content" source="./media/about-iot-edge/cloud-interface.png" alt-text="Diagram of how device telemetry and actions are coordinated with the cloud.":::
+:::image type="content" source="./media/about-iot-edge/cloud-interface.png" alt-text="Diagram of how device data and actions are coordinated with the cloud.":::
 
 ## Next steps
 
-Try out IoT Edge concepts by deploying your first IoT Edge module to a device:
+Take the next step learning IoT Edge concepts by deploying your first IoT Edge module to a device:
 
 * [Deploy modules to a Linux IoT Edge device](quickstart-linux.md)
 * [Deploy modules to a Windows IoT Edge device](quickstart.md)

articles/iot-edge/iot-edge-modules.md

@@ -1,21 +1,25 @@
 ---
-title: Learn how modules run logic on your devices - Azure IoT Edge | Microsoft Docs 
-description: Azure IoT Edge modules are containerized units of logic that can be deployed and managed remotely so that you can run business logic on IoT Edge devices
+title: How Azure IoT Edge Modules Run Logic on Devices
+description: Learn how Azure IoT Edge modules run logic on devices, using containerized applications, and secure communication with IoT Hub.
 author: PatAltimore
-
 ms.author: patricka
-ms.date: 03/21/2019
+ms.date: 03/20/2025
 ms.topic: conceptual
 ms.service: azure-iot-edge
 services: iot-edge
-ms.custom: devx-track-csharp
+ms.custom:
+  - devx-track-csharp
+  - ai-gen-docs-bap
+  - ai-gen-title
+  - ai-gen-description
+#customer intent: As a developer, I want to understand how Azure IoT Edge modules run logic on devices so that I can design and deploy edge solutions effectively.
 ---
 
 # Understand Azure IoT Edge modules
 
 [!INCLUDE [iot-edge-version-all-supported](includes/iot-edge-version-all-supported.md)]
 
-Azure IoT Edge lets you deploy and manage business logic on the edge in the form of *modules*. Azure IoT Edge modules are the smallest unit of computation managed by IoT Edge, and can contain Azure services (such as Azure Stream Analytics) or your own solution-specific code. To understand how modules are developed, deployed, and maintained, consider the four conceptual elements of a module:
+Azure IoT Edge lets you deploy and manage business logic on edge devices using *modules*. Azure IoT Edge modules are the smallest unit of computation managed by IoT Edge, and can contain Azure services (such as Azure Stream Analytics) or your own solution-specific code. To understand how modules are developed, deployed, and maintained, consider the four conceptual elements of a module:
 
 * A **module image** is a package containing the software that defines a module.
 * A **module instance** is the specific unit of computation running the module image on an IoT Edge device. The module instance is started by the IoT Edge runtime.
@@ -25,37 +29,33 @@ Azure IoT Edge lets you deploy and manage business logic on the edge in the form
 ## Module images and instances
 
 IoT Edge module images contain applications that take advantage of the management, security, and communication features of the IoT Edge runtime. You can develop your own module images, or export one from a supported Azure service, such as Azure Stream Analytics.
-The images exist in the cloud and they can be updated, changed, and deployed in different solutions. For instance, a module that uses machine learning to predict production line output exists as a separate image than a module that uses computer vision to control a drone.
+The images exist in the cloud, and you can update, change, and deploy them in different solutions. For example, a module using machine learning to predict production line output is a separate image from a module using computer vision to control a drone.
 
-Each time a module image is deployed to a device and started by the IoT Edge runtime, a new instance of that module is created. Two devices in different parts of the world could use the same module image. However, each device would have its own module instance when the module is started on the device.
+Each time the IoT Edge runtime deploys and starts a module image on a device, it creates a new instance of that module. Two devices in different parts of the world could use the same module image. However, each device would have its own module instance when the module is started on the device.
 
 ![Diagram - Module images in cloud, module instances on devices](./media/iot-edge-modules/image_instance.png)
 
 In implementation, modules images exist as container images in a repository, and module instances are containers on devices.
 
-<!--
-As use cases for Azure IoT Edge grow, new types of module images and instances will be created. For example, resource constrained devices cannot run containers so may require module images that exist as dynamic link libraries and instances that are executables. 
--->
-
 ## Module identities
 
-When a new module instance is created by the IoT Edge runtime, it gets a corresponding module identity. The module identity is stored in IoT Hub, and is used as the addressing and security scope for all local and cloud communications for that module instance.
+When the IoT Edge runtime creates a new module instance, it assigns a corresponding module identity. IoT Hub stores the module identity, which serves as the addressing and security scope for all local and cloud communications for the module instance.
 
-The identity associated with a module instance depends on the identity of the device on which the instance is running and the name you provide to that module in your solution. For instance, if you call `insight` a module that uses an Azure Stream Analytics, and you deploy it on a device called `Hannover01`, the IoT Edge runtime creates a corresponding module identity called `/devices/Hannover01/modules/insight`.
+The module instance's identity depends on the device's identity and the name you assign to the module in your solution. For example, if you name a module `insight` and deploy it on a device called `Hannover01`, the IoT Edge runtime creates a corresponding module identity called `/devices/Hannover01/modules/insight`.
 
-Clearly, in scenarios when you need to deploy one module image multiple times on the same device, you can deploy the same image multiple times with different names.
+In scenarios where you need to deploy one module image multiple times on the same device, you can deploy it with different names.
 
 ![Diagram - Module identities are unique within devices and across devices](./media/iot-edge-modules/identity.png)
 
 ## Module twins
 
-Each module instance also has a corresponding module twin that you can use to configure the module instance. The instance and the twin are associated with each other through the module identity.
+Each module instance has a corresponding module twin you use to configure it. The module identity links the instance and the twin.
 
-A module twin is a JSON document that stores module information and configuration properties. This concept parallels the [device twin](../iot-hub/iot-hub-devguide-device-twins.md) concept from IoT Hub. The structure of a module twin is the same as a device twin. The APIs used to interact with both types of twins are also the same. The only difference between the two is the identity used to instantiate the client SDK.
+A module twin is a JSON document that stores module information and configuration properties. This concept parallels the [device twin](../iot-hub/iot-hub-devguide-device-twins.md) concept from IoT Hub. A module twin's structure is the same as a device twin's. The APIs for interacting with both types of twins are the same. The only difference between the two is the identity used to instantiate the client SDK.
 
 ```csharp
 // Create a ModuleClient object. This ModuleClient will act on behalf of a
-// module since it is created with a module’s connection string instead
+// module since it is created with a module's connection string instead
 // of a device connection string.
 ModuleClient client = new ModuleClient.CreateFromEnvironmentAsync(settings);
 await client.OpenAsync();
@@ -65,7 +65,7 @@ Twin twin = await client.GetTwinAsync();
 ```
 ## Offline capabilities
 
-Azure IoT Edge modules can operate offline indefinitely after syncing with IoT Hub at least once. IoT Edge devices can also extend this offline capability to other IoT devices. For more information, see [Understand extended offline capabilities for IoT Edge devices, modules, and downstream devices](offline-capabilities.md).
+Azure IoT Edge modules operate offline indefinitely after syncing with IoT Hub once. IoT Edge devices can also extend this offline capability to other IoT devices. For more information, see [Understand extended offline capabilities for IoT Edge devices, modules, and downstream devices](offline-capabilities.md).
 
 ## Next steps