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🚀 Deployment Workshop

Note: This workshop was conducted using B&RDK Github, which can be cloned from:

🔗 GitHub Repository

The latest commit on the main branch now contains the complete solution, so some steps in the guide below may no longer be necessary.

1. Setup Web and FTP Server​

Create an .env file​

Create an .env file and fill it with the necessary information. Use example.env as a reference.

Configure docker-compose.yml​

In docker-compose.yml, set your environment variables using the syntax:

{$ENVIRONMENT_VAR_NAME}

Read through the docker-compose.yml file and try to understand each line. Consider the following questions:

  • ❓ What is the difference between the FTP and web container images?
  • ❓ Why do we use volumes?

▶️ Run the Containers​

Run the following command in the terminal to start the containers:

docker-compose up

🌍 Interact with the Frontend​

Once the containers are running, open the frontend in your browser at:

http://<EDGE_IP>:5000

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Browse​

Explore the available B&R PLCs on the network.

Add a New Device​

Use the interface to add a new device by specifying its IP address.

Upload Updates​

Upload updates from the TestUpdates folder.

Delete an Update​

Remove an update using the frontend controls.

Send an Update to a PLC​

Try sending an update to a PLC. Use the shared PLC with IP address:

192.168.30.100

2. Pull Updates in PLC​

Open the Automation Studio Project​

Open the Automation Studio 4.12 project located in the PLC directory.

Connect to the PLC​

The project is already downloaded. Open monitor mode on IP:

192.168.30.100

Program Features​

The program reads the current software version in INIT using ArProjectGetInfo. Additionally, it can:

  • 📥 Download Update from the Edge FTP server to the PLC FTP server.
  • 🔄 Check Version of the update on the PLC FTP server.
  • 🚀 Execute Update on the PLC FTP server.

Play Around with the Commands​

Experiment with the different commands, but NOTE: Since we are sharing one PLC, you should only trigger a command if state = 10 (waiting state).

If you experience that state=222 it is an error state and can be cleared using reset=TRUE . It then return to state=10

3. Build Your Own OPC UA Image and Add It to docker-compose​

📂 Locate the OPC UA Client​

In the OpcuaClient directory, you will find the opcuaclient.py script, which polls and reads some nodes every 2 seconds. The nodes it will read are defined in nodesToRead.json. Your task is to Dockerize this OPC UA client.

📝 Create a Dockerfile​

First, create a Dockerfile for the OPC UA client. You can look at the Dockerfile for the web server as inspiration. Note: Your Dockerfile needs to install asyncua, as this library is not included in Python by default:

# Install required dependencies
RUN pip install asyncua

Try to figure out out the rest by yourself.

🔨 Build and Run the Docker Image​

Navigate to the OpcuaClient directory and build the Docker image:

cd OpcuaClient
docker build -t opcua-client .

You can then run your newly created image:

docker run --rm opcua-client

The --rm flag ensures the container is removed after it stops.

If everything works you should see the OPC UA nodes in the terminal.

🏗️ Add the Image to docker-compose.yml​

Now, integrate the new Docker image into your docker-compose.yml. To do this:

  1. Copy the existing web: container configuration.
  2. Rename it to something like opcuaclient:.
  3. Since the Dockerfile is not in the same directory as docker-compose.yml, modify the build section as follows:
opcuaclient:
  build:
    context: ./OpcuaClient
    dockerfile: Dockerfile

Try to figure out the rest.

▶️ Run All Containers Together​

Once everything is set up, start all three containers:

docker-compose up -d

🎉 Enjoy your creation! 😃