Tutorial: Develop IoT Edge modules with Linux containers using IoT Edge for Linux on Windows

Applies to: yes icon IoT Edge 1.1 Other versions: IoT Edge 1.3, IoT Edge 1.4

Applies to: IoT Edge 1.3 checkmark IoT Edge 1.3 IoT Edge 1.4 checkmark IoT Edge 1.4 Other versions: IoT Edge 1.1

Use Visual Studio 2019 to develop, debug and deploy code to devices running IoT Edge for Linux on Windows.

This tutorial walks through developing, debugging and deploying your own code to an IoT Edge device using IoT Edge for Linux on Windows. This article is a useful prerequisite for the other tutorials, which go into more detail about specific programming languages or Azure services.

This tutorial uses the example of deploying a C# module to a Linux device. This example was chosen because it's the most common developer scenario for IoT Edge solutions. Even if you plan on using a different language or deploying an Azure service, this tutorial is still useful to learn about the development tools and concepts. Complete this introduction to the development process, then choose your preferred language or Azure service to dive into the details.

In this tutorial, you learn how to:

  • Set up your development machine.
  • Use the IoT Edge tools for Visual Studio Code to create a new project.
  • Build your project as a container and store it in an Azure container registry.
  • Deploy your code to an IoT Edge device.

Prerequisites

This article assumes that you use a machine running Windows as your development machine. On Windows computers, you can develop either Windows or Linux modules. This tutorial will guide you through the development of Linux containers, using IoT Edge for Linux on Windows for building and deploying the modules.

Install Visual Studio on your development machine. Make sure you include the Azure development and Desktop development with C# workloads in your Visual Studio 2019 installation. You can Modify Visual Studio 2019 to add the required workloads.

After your Visual Studio 2019 is ready, you also need the following tools and components:

  • Download and install Azure IoT Edge Tools from the Visual Studio marketplace to create an IoT Edge project in Visual Studio 2019.

    Tip

    If you are using Visual Studio 2017, download and install Azure IoT Edge Tools for VS 2017 from the Visual Studio marketplace

Cloud resources:

  • A free or standard-tier IoT hub in Azure.

If you don't have an Azure subscription, create an Azure free account before you begin.

Check your tools version

  1. From the Extensions menu, select Manage Extensions. Expand Installed > Tools and you can find Azure IoT Edge Tools for Visual Studio and Cloud Explorer for Visual Studio.

  2. Note the installed version. You can compare this version with the latest version on Visual Studio Marketplace (Cloud Explorer, Azure IoT Edge)

  3. If your version is older than what's available on Visual Studio Marketplace, update your tools in Visual Studio as shown in the following section.

Note

If you are using Visual Studio 2022, Cloud Explorer is retired. To deploy Azure IoT Edge modules, use Azure CLI or Azure portal.

Update your tools

  1. In the Manage Extensions window, expand Updates > Visual Studio Marketplace, select Azure IoT Edge Tools or Cloud Explorer for Visual Studio and select Update.

  2. After the tools update is downloaded, close Visual Studio to trigger the tools update using the VSIX installer.

  3. In the installer, select OK to start and then Modify to update the tools.

  4. After the update is complete, select Close and restart Visual Studio.

Key concepts

This tutorial walks through the development of an IoT Edge module. An IoT Edge module, or sometimes just module for short, is a container with executable code. You can deploy one or more modules to an IoT Edge device. Modules perform specific tasks like ingesting data from sensors, cleaning and analyzing data, or sending messages to an IoT hub. For more information, see Understand Azure IoT Edge modules.

When developing IoT Edge modules, it's important to understand the difference between the development machine and the target IoT Edge device where the module will eventually be deployed. The container that you build to hold your module code must match the operating system (OS) of the target device. For example, the most common scenario is someone developing a module on a Windows computer intending to target a Linux device running IoT Edge. In that case, the container operating system would be Linux. As you go through this tutorial, keep in mind the difference between the development machine OS and the container OS. For this tutorial, you'll be using your Windows host for development and the IoT Edge for Linux on Windows (EFLOW) VM for building and deploying the modules.

This tutorial targets devices running IoT Edge with Linux containers. You can use your preferred operating system as long as your development machine runs Linux containers. We recommend using Visual Studio to develop with Linux containers, so that's what this tutorial will use. You can use Visual Studio Code as well, although there are differences in support between the two tools. For more information, refer to Tutorial: Develop IoT Edge modules with Linux containers.

Set up docker-cli and Docker engine remote connection

IoT Edge modules are packaged as containers, so you need a container engine on your development machine to build and manage them. The EFLOW virtual machine already contains an instance of Docker engine, so this tutorial will guide on how to remotely connect from the Windows developer machine to the EFLOW VM Docker instance. By using this, we remove the dependency on Docker Desktop for Windows.

The first step is to configure docker-cli on the Windows development machine to be able to connect to the remote docker engine.

  1. Download the precompiled docker.exe version of the docker-cli from docker-cli Chocolatey. You can also download the official cli project from docker/cli GitHub and compile it following the repo instructions.
  2. Extract the docker.exe to a directory in your development machine. For example, C:\Docker\bin
  3. Open About your PC -> System Info -> Advanced system settings
  4. Select Advanced -> Environment variables -> Under User variables check Path
  5. Edit the Path variable and add the location of the docker.exe
  6. Open an elevated PowerShell session
  7. Check that Docker CLI is accessible using the command
    docker --version
    

If everything was successfully configurated, the previous command should output the docker version, something like Docker version 20.10.12, build e91ed57.

The second step is to configure the EFLOW virtual machine Docker engine to accept external connections, and add the appropriate firewall rules.

Warning

Exposing Docker engine to external connections may increase security risks. This configuration should only be used for development purposes. Make sure to revert the configuration to default settings after development is finished.

  1. Open an elevated PowerShell session and run the following commands

    # Configure the EFLOW virtual machine Docker engine to accept external connections, and add the appropriate firewall rules.
    Invoke-EflowVmCommand "sudo iptables -A INPUT -p tcp --dport 2375 -j ACCEPT"
    
    # Create a copy of the EFLOW VM _docker.service_ in the system folder.
    Invoke-EflowVmCommand "sudo cp /lib/systemd/system/docker.service /etc/systemd/system/docker.service"
    
    # Replace the service execution line to listen for external connections.
    Invoke-EflowVmCommand "sudo sed -i 's/-H fd:\/\// -H fd:\/\/ -H tcp:\/\/0.0.0.0:2375/g'  /etc/systemd/system/docker.service"
    
    # Reload the EFLOW VM services configurations.
    Invoke-EflowVmCommand "sudo systemctl daemon-reload"
    
    # Reload the Docker engine service.
    Invoke-EflowVmCommand "sudo systemctl restart docker.service"
    
    # Check that the Docker engine is listening to external connections.
    Invoke-EflowVmCommand "sudo netstat -lntp | grep dockerd"
    

    The following is example output.

    PS C:\> # Configure the EFLOW virtual machine Docker engine to accept external connections, and add the appropriate firewall rules.
    PS C:\> Invoke-EflowVmCommand "sudo iptables -A INPUT -p tcp --dport 2375 -j ACCEPT"
    PS C:\>
    PS C:\> # Create a copy of the EFLOW VM docker.service in the system folder.
    PS C:\> Invoke-EflowVmCommand "sudo cp /lib/systemd/system/docker.service /etc/systemd/system/docker.service"
    PS C:\>
    PS C:\> # Replace the service execution line to listen for external connections.
    PS C:\> Invoke-EflowVmCommand "sudo sed -i 's/-H fd:\/\// -H fd:\/\/ -H tcp:\/\/0.0.0.0:2375/g' /etc/systemd/system/docker.service"
    PS C:\>
    PS C:\> # Reload the EFLOW VM services configurations.
    PS C:\> Invoke-EflowVmCommand "sudo systemctl daemon-reload"
    PS C:\>
    PS C:\> # Reload the Docker engine service.
    PS C:\> Invoke-EflowVmCommand "sudo systemctl restart docker.service"
    PS C:\>
    PS C:\> # Check that the Docker engine is listening to external connections.
    PS C:\> Invoke-EflowVmCommand "sudo netstat -lntp | grep dockerd"
    tcp6       0      0 :::2375                 :::*                    LISTEN      2790/dockerd
    
  2. The final step is to test the Docker connection to the EFLOW VM Docker engine. First, you will need the EFLOW VM IP address.

    Get-EflowVmAddr
    

    Tip

    If the EFLOW VM was deployed without Static IP, the IP address may change across Windows host OS reboots or networking changes. Make sure you are using the correct EFLOW VM IP address every time you want to establish a remote Docker engine connection.

    The following is example output.

    PS C:\> Get-EflowVmAddr
    [03/15/2022 15:22:30] Querying IP and MAC addresses from virtual machine (DESKTOP-J1842A1-EFLOW)
     - Virtual machine MAC: 00:15:5d:6f:da:78
     - Virtual machine IP : 172.31.24.105 retrieved directly from virtual machine
    00:15:5d:6f:da:78
    172.31.24.105 
    
  3. Using the obtained IP address, connect to the EFLOW VM Docker engine, and run the Hello-World sample container.Replace <EFLOW-VM-IP> with the EFLOW VM IP address obtained in the previous step.

    docker -H tcp://<EFLOW-VM-IP>:2375 run --rm hello-world
    

    You should see that the container is being downloaded, and after will run and output the following.

    PS C:\> docker -H tcp://172.31.24.105:2375 run --rm hello-world
    Unable to find image 'hello-world:latest' locally
    latest: Pulling from library/hello-world
    2db29710123e: Pull complete
    Digest: sha256:4c5f3db4f8a54eb1e017c385f683a2de6e06f75be442dc32698c9bbe6c861edd
    Status: Downloaded newer image for hello-world:latest
    
    Hello from Docker!
    This message shows that your installation appears to be working correctly.
    
    To generate this message, Docker took the following steps:
     1. The Docker client contacted the Docker daemon.
     2. The Docker daemon pulled the "hello-world" image from the Docker Hub.
        (amd64)
     3. The Docker daemon created a new container from that image which runs the
        executable that produces the output you are currently reading.
     4. The Docker daemon streamed that output to the Docker client, which sent it
        to your terminal.
    
    To try something more ambitious, you can run an Ubuntu container with:
     $ docker run -it ubuntu bash
    
    Share images, automate workflows, and more with a free Docker ID:
     https://hub.docker.com/
    
    For more examples and ideas, visit:
     https://docs.docker.com/get-started/
    

Create an Azure IoT Edge project

The IoT Edge project template in Visual Studio creates a solution that can be deployed to IoT Edge devices. First you create an Azure IoT Edge solution, and then you generate the first module in that solution. Each IoT Edge solution can contain more than one module.

Tip

The IoT Edge project structure created by Visual Studio is not the same as in Visual Studio Code.

  1. In Visual Studio, create a new project.

  2. On the Create a new project page, search for Azure IoT Edge. Select the project that matches the platform (Linux IoT Edge module) and architecture for your IoT Edge device, and select Next.

    Create New Project

  3. On the Configure your new project page, enter a name for your project and specify the location, then select Create.

  4. On the Add Module window, select the type of module you want to develop. You can also select Existing module to add an existing IoT Edge module to your deployment. Specify your module name and module image repository.

    Visual Studio autopopulates the repository URL with localhost:5000/<module name>. If you use a local Docker registry for testing, then localhost is fine. If you use Azure Container Registry, then replace localhost:5000 with the log in server from your registry's settings. The login server looks like <registry name>.azurecr.io.The final result should look like <registry name>.azurecr.io/<module name>.

    Select Add to add your module to the project.

    Screenshot of adding how to add an application and module to Visual Studio solution

Now, you have an IoT Edge project and an IoT Edge module in your Visual Studio solution.

The module folder contains a file for your module code, named either program.cs or main.c depending on the language you chose. This folder also contains a file named module.json that describes the metadata of your module. Various Docker files provide the information needed to build your module as a Windows or Linux container.

The project folder contains a list of all the modules included in that project. Right now it should show only one module, but you can add more.

The project folder also contains a file named deployment.template.json. This file is a template of an IoT Edge deployment manifest, which defines all the modules that will run on a device along with how they'll communicate with each other. For more information about deployment manifests, see Learn how to deploy modules and establish routes. If you open this deployment template, you see that the two runtime modules, edgeAgent and edgeHub are included, along with the custom module that you created in this Visual Studio project. A fourth module named SimulatedTemperatureSensor is also included. This default module generates simulated data that you can use to test your modules, or delete if it's not necessary. To see how the simulated temperature sensor works, view the SimulatedTemperatureSensor.csproj source code.

Set IoT Edge runtime version

The IoT Edge extension defaults to the latest stable version of the IoT Edge runtime when it creates your deployment assets. Currently, the latest stable version is version 1.2. If you're developing modules for devices running the 1.1 long-term support version or the earlier 1.0 version, update the IoT Edge runtime version in Visual Studio to match.

  1. In the Solution Explorer, right-click the name of your project and select Set IoT Edge runtime version.

    Right-click your project name and select set IoT Edge runtime version.

  2. Use the drop-down menu to choose the runtime version that your IoT Edge devices are running, then select OK to save your changes.

  3. Re-generate your deployment manifest with the new runtime version. Right-click the name of your project and select Generate deployment for IoT Edge.

Warning

If you are chaging the IoT Edge runtime version, make sure the deploymnet templates reflect the necessary changes. Currently there's a known issue with Azure IoT Edge Tools, that won't change the "schemVersion" inside the "properties.desired" object of "$edgeHub" module (last section of the json file).

Set up Visual Studio 2019 remote Docker engine instance

Use the Azure IoT Edge tools extensions for Visual Studio Code to IoT Edge modules and configure it to use the remote Docker engine running inside the EFLOW virtual machine.

  1. Select Tools -> Azure IoT Edge tools -> IoT Edge tools settings...

  2. Replace the DOCKER_HOST localhost value with the EFLOW VM IP address. If you don't remember the IP address, use the EFLOW PowerShell cmdlet Get-EflowVmAddr to obtain it. For exmaple, if the EFLOW VM IP address is 172.20.1.100, then the new value should be tcp://172.20.1.100:2375.

    Screenshot of IoT Edge Tools settings

  3. Select OK

Develop your module

When you add a new module, it comes with default code that is ready to be built and deployed to a device so that you can start testing without touching any code. The module code is located within the module folder in a file named Program.cs (for C#) or main.c (for C).

The default solution is built so that the simulated data from the SimulatedTemperatureSensor module is routed to your module, which takes the input and then sends it to IoT Hub.

When you're ready to customize the module template with your own code, use the Azure IoT Hub SDKs to build other modules that address the key needs for IoT solutions such as security, device management, and reliability.

Build and push a single module

Typically, you'll want to test and debug each module before running it within an entire solution with multiple modules. Because the solution will be build or debug using the Docker engine running inside the EFLOW VM, the first step will be building and publishing the module to enable remote debugging.

  1. In Solution Explorer, right-click the module folder and select Set as StartUp Project from the menu.

    Screenshot of setting the start-up project

  2. To debug the C# Linux module, we need to update Dockerfile.amd64.debug to enable SSH service. Update the Dockerfile.amd64.debug file to use the following template: Dockerfile for Azure IoT Edge AMD64 C# Module with Remote Debug Support.

    Note

    When choosing Debug, Visual Studio uses Dockerfile.(amd64|windows-amd64).debug to build Docker images. This includes the .NET Core command-line debugger VSDBG in your container image while building it. For production-ready IoT Edge modules, we recommend that you use the Release configuration, which uses Dockerfile.(amd64|windows-amd64) without VSDBG.

    Warning

    Make sure the last line of the template ENTRYPOINT ["dotnet", "IotEdgeModule1.dll"] the name of the DLL matches the name of your IoT Edge module project.

    Screenshot of setting the Dockerfile template

  3. To establish an SSH connection with the Linux module, we need to create an RSA key. Open an elevated PowerShell session and run the following commands to create a new RSA key. Make sure you save the RSA key under the same IoT Edge module folder, and the name of the key is id_rsa.

    ssh-keygen -t RSA -b 4096 -m PEM
    

    Screenshot of how to create an SSH key

  4. If you're using a private registry like Azure Container Registry (ACR), use the following Docker command to sign in to it. You can get the username and password from the Access keys page of your registry in the Azure portal. If you're using local registry, you can run a local registry.

    docker -H tcp://<EFLOW-VM-IP>:2375 login -u <ACR username> -p <ACR password> <ACR login server>
    
  5. In Solution Explorer, right-click the project folder and select Build and Push IoT Edge Modules to build and push the Docker image for each module.

Deploy and debug the solution

  1. If you're using a private registry like Azure Container Registry, you need to add your registry login information to the runtime settings found in the file deployment.template.json. Replace the placeholders with your actual ACR admin username, password, and registry name.

          "settings": {
            "minDockerVersion": "v1.25",
            "loggingOptions": "",
            "registryCredentials": {
              "registry1": {
                "username": "<username>",
                "password": "<password>",
                "address": "<registry name>.azurecr.io"
              }
            }
          }
    

    Note

    This article uses admin login credentials for Azure Container Registry, which are convenient for development and test scenarios. When you're ready for production scenarios, we recommend a least-privilege authentication option like service principals. For more information, see Manage access to your container registry.

  2. It's necessary to expose port 22 to access the module SSH service. This tutorial uses 10022 as the host port, but you may specify a different port, which will be used as an SSH port to connect into the Linux C# module. You need to add the SSH port information to the "createOptions" of this Linux module setting found in the file deployment.debug.template.json.

         "createOptions": {
            "HostConfig": {
               "Privileged": true,
               "PortBindings": {
                     "22/tcp": [
                        {
                           "HostPort": "10022"
                        }
                     ]
               }
            }
         }
    
  3. In Solution Explorer, right-click the project folder and select Generate Deployment for IoT Edge to build the new IoT Edge deployment json.

  4. Open Cloud Explorer by clicking View > Cloud Explorer. Make sure you've logged in to Visual Studio 2019.

  5. In Cloud Explorer, expand your subscription, find your Azure IoT Hub and the Azure IoT Edge device you want to deploy.

  6. Right-click on the IoT Edge device and choose Create deployment. Navigate to the debug deployment manifest configured for your platform located in the config folder in your Visual Studio solution, such as deployment.amd64.json.

  7. In Cloud Explorer, right-click your edge device and refresh to see the new module running along with $edgeAgent and $edgeHub modules.

  8. Using and elevated PowerShell session run the following commands

    1. Get the moduleId based on the name used for the Linux C# module. Make sure to replace the <iot-edge-module-name> placeholder with your module's name.

      $moduleId = Invoke-EflowVmCommand "sudo docker ps -aqf name=<iot-edge-module-name>"
      
    2. Check that the $moduleId is correct – If the variable is empty, make sure you’re using the correct module name

    3. Start the SSH service inside the Linux container

      Invoke-EflowVmCommand "sudo docker exec -it -d $moduleId service ssh start"
      
    4. Open the module SSH port on the EFLOW VM (this tutorial uses port 10022)

      Invoke-EflowVmCommand "sudo iptables -A INPUT -p tcp --dport 10022 -j ACCEPT"
      

    Warning

    For security reasons, every time the EFLOW VM reboots, the IP table rule will delete and go back to the original settings. Also, the module SSH service will have to be started again manually.

  9. After successfully starting SSH service, select Debug -> Attach to Process, set Connection Type to SSH, and Connection target to the IP address of your EFLOW VM. If you don’t know the EFLOW VM IP, you can use the Get-EflowVmAddr PowerShell cmdlet. First, type the IP and then press enter. In the pop-up window, input the following configurations:

    Field Value
    Hostname Use the EFLOW VM IP
    Port 10022 (Or the one you used in your deployment configuration)
    Username root
    Authentication type Private Key
    Private Key File Full path to the id_rsa that was previously created in Step 5
    Passphrase The one used for the key created in Step 5

    Screenshot of how to connect to a remote system

  10. After successfully connecting to the module using SSH, then you can choose the process and select Attach. For the C# module you need to choose process dotnet and Attach to to Managed (CoreCLR). It may take 10/C20 seconds the first time you do so.

    Screenshot of how to attach an edge module process.

  11. Set a breakpoint to inspect the module.

    • If developing in C#, set a breakpoint in the PipeMessage() function in Program.cs.
    • If using C, set a breakpoint in the InputQueue1Callback() function in main.c.
  12. The output of the SimulatedTemperatureSensor should be redirected to input1 of the custom Linux C# module. The breakpoint should be triggered. You can watch variables in the Visual Studio Locals window.

    Screenshot of how to debug a single module

  13. Press Ctrl + F5 or select the stop button to stop debugging.

Clean up resources

If you plan to continue to the next recommended article, you can keep the resources and configurations that you created and reuse them. You can also keep using the same IoT Edge device as a test device.

Otherwise, you can delete the local configurations and the Azure resources that you used in this article to avoid charges.

Delete Azure resources

Deleting Azure resources and resource groups is irreversible. Make sure that you don't accidentally delete the wrong resource group or resources. If you created the IoT hub inside an existing resource group that has resources that you want to keep, delete only the IoT hub resource itself, not the resource group.

To delete the resources:

  1. Sign in to the Azure portal, and then select Resource groups.

  2. Select the name of the resource group that contains your IoT Edge test resources.

  3. Review the list of resources that are contained in your resource group. If you want to delete all of them, you can select Delete resource group. If you want to delete only some of them, you can click into each resource to delete them individually.

Next steps

In this tutorial, you set up Visual Studio on your development machine and deployed and debugged your first IoT Edge module from it. Now that you know the basic concepts, try adding functionality to a module so that it can analyze the data passing through it. Choose your preferred language: