PLC to Cloud via HiveMQ (Edge + Cloud) — OPC UA → MQTT → Confluent

Read PLC via OPC UA, map to MQTT with HiveMQ Edge, bridge to HiveMQ Cloud, and stream to Confluent (Kafka).

Sending PLC data to Cloud (Kafka) makes machine data available in real-time for dashboards, analytics, and cloud applications. It keeps the PLC focused on control, while Kafka distributes the data to multiple systems simultaneously.

Why send PLC data to Cloud (Kafka)?

PLC data (temperatures, counts, states, and alarms) is valuable, but PLCs are designed for machine control, not for handling large amounts of data or integrating with cloud systems.

By streaming PLC data into Kafka (via HiveMQ), you get:

• Scalability – Kafka can handle millions of events per second from many PLCs and machines.

• Integration – Kafka acts as a hub, making PLC data accessible to cloud applications, analytics platforms, databases, AI/ML pipelines, and more.

• Real-time processing – Process machine data as it happens (predictive maintenance, quality checks, dashboards).

• Decoupling – PLCs stay focused on control, while Kafka distributes the data to any number of consumers without overloading the PLC.

👉 In short: Kafka turns raw PLC data into a real-time data stream for enterprise systems and analytics.

Information flow

1. Read PLC data via OPC UA

First, we read raw data from the Siemens S7-1500 PLC via OPC UA. The Siemens PLC acts as an OPC UA server, and the Edge device acts as an OPC UA client. The Revolution Pi acts as an Edge device, running HiveMQ Edge —a software-based Edge MQTT Gateway that features several protocol adaptors. We use an OPC UA adaptor that reads directly from the Siemens S7-1500 PLC.

LIVE Tag value in TIA Portal Online view

Configuration of OPC UA tag in HiveMQ Edge

2. Data mapping

Map OPC UA tags to MQTT topics in HiveMQ Edge, which means now we have the data streaming to the defined MQTT topic of the MQTT broker running locally in the Revolution Pi.

Data mapping from OPC UA to MQTT in HiveMQ Edge

3. MQTT Bridge

HiveMQ Edge bridges the local MQTT broker (located on the Edge) to the HiveMQ Cloud broker, enabling the global sharing of data via a secure network.

Local MQTT Broker --> Cloud MQTT Broker in HiveMQ Edge

4. Topic Filter

To bridge the data from the local MQTT broker to the Cloud MQTT broker, we need to add a topic filter to the MQTT Bridge connection.

Using the filter as shown above will send the data to the Cloud MQTT Broker with the same topic as declared in the local MQTT broker, as shown below:

5. HiveMQ Cloud to Kafka

HiveMQ Cloud forwards MQTT messages to Kafka topics (Confluent) using the Kafka protocol, with a ready-to-use integration in the platform. HiveMQ Cloud’s Confluent/Kafka integration forwards MQTT messages to Kafka using the Kafka protocol, not MQTT.

Bootstrap server link of the Cluster in Confluent

Api Key and secret of Cluster in Confluent

MQTT Topic --> Kafka Topic in HiveMQ Cloud

How to install HiveMQ Edge in Revolution Pi?

1

Download the HiveMQ Edge package in Revolution Pi.

#move to opt directory
cd /
cd opt
#download the HiveMQ package
sudo curl -O https://www.hivemq.com/releases/edge/hivemq-edge-full-2025.15.zip

2

Install Java (if not installed)

sudo apt update
sudo apt install -y openjdk-17-jre-headless

3

Install unzip (if not pre-installed)

sudo apt update
sudo apt install unzip -y

4

Unzip the package

sudo unzip hivemq-edge-full-2025.15.zip

5

Create a HiveMQ symbolic link (symlink):

sudo ln -s /opt/hivemq-edge-full-2025.15 /opt/hivemq

6

Create a HiveMQ user:

sudo useradd -d /opt/hivemq hivemq

7

Make scripts executable and change the owner to the hivemq user:

sudo chown -R hivemq:hivemq /opt/hivemq-edge-2025.15
sudo chown -R hivemq:hivemq /opt/hivemq
cd /opt/hivemq-edge-2025.15
sudo chmod +x ./bin/run.sh

8

Install the init script (optional). For Debian-based Linux distributions such as Debian, Ubuntu, or Raspbian that use init.d scripts:

sudo cp /opt/hivemq/bin/init-script/hivemq-debian /etc/init.d/hivemq
sudo chmod +x /etc/init.d/hivemq

9

Start HiveMQ on boot (optional)

sudo systemctl enable hivemq

10

Start HiveMQ

cd /opt/hivemq-edge-2025.15
sudo ./bin/run.sh

11

Log in to HiveMQ Edge Web UI

Once you start a HiveMQ Edge instance, you can access the HiveMQ Edge administrative console in your Edge device browser at http://localhost:8080. The default username is "admin", and the default password is "hivemq". If you want to view the Web UI on your computer remotely, you can set up an SSH Tunnel. In your computer, run the following code in the terminal

ssh -L 8080:localhost:8080 [email protected]

Now you can access the HiveMQ Edge Web UI by opening localhost:8080. Log in usingthe default credentials, username: admin and password: hivemq

WebUI of HiveMQ Edge running in Revolution Pi

Abbreviations & Terms

• OPC UA (Open Platform Communications – Unified Architecture) A machine-to-machine communication protocol for industrial automation. Used to read/write real-time data from PLCs, sensors, and devices.

• MQTT (Message Queuing Telemetry Transport) A lightweight publish/subscribe messaging protocol, ideal for IoT devices and edge communication.

• Edge Device A device placed close to machines (e.g., Revolution Pi) that collects and forwards data, often translating from one protocol to another.

• HiveMQ HiveMQ is the proven MQTT IoT data streaming platform for secure, real-time data connectivity, enabling more intelligent decisions and digital transformation. Learn more here

• HiveMQ Edge / HiveMQ Cloud

  • HiveMQ Edge: Runs locally (on Raspberry Pi / RevPi) to connect industrial protocols, such as OPC UA, to MQTT.

  • HiveMQ Cloud: Managed MQTT broker in the cloud, used for scalable IoT data exchange.

• Kafka (Apache Kafka) It’s basically a high-performance message bus that can handle millions of messages per second. It’s used to publish, store, process, and subscribe to streams of events (such as sensor data, logs, and transactions).

• Confluent A managed cloud service built on Apache Kafka, providing Kafka clusters plus enterprise features like security, monitoring, and connectors. So instead of running Kafka yourself (which can be complex), you can use Confluent’s hosted Kafka clusters.

Debug

• No javaruntime installed error!

sudo apt update
sudo apt install -y openjdk-17-jre-headless

• Port 1883 occupied

sudo netstat -tulpn | grep :1883
#You will get output like this
#tcp   LISTEN   0   128   0.0.0.0:1883   0.0.0.0:*   1234/mosquitto
sudo kill -9 1234 #kill service with specific PID

♥️ Work With Me

I regularly test industrial automation and IIoT devices. If you’d like me to review your product or showcase it in my courses and YouTube channel:

📧 Email: [email protected] or drop me a message on LinkedIn