Getting started with HiveMQ Platform

The HiveMQ Platform creates a trusted path from MQTT data streaming to real-time data intelligence and governed action.

This guide shows you how to deploy a HiveMQ broker, stream test data to it, and begin to explore the data intelligence capabilities of HiveMQ Platform.

HiveMQ Platform replaces the HiveMQ Cloud Console as the default HiveMQ management experience. Newly created HiveMQ accounts open in the HiveMQ Platform automatically. Existing HiveMQ Cloud customers move over in stages, and you can switch back to the legacy Console during the transition.

What you need

  • Docker installed and running on your computer.

  • A terminal.

  • An email address, or a GitHub, Google, or LinkedIn account.

What you accomplish

  • Create a HiveMQ account.

  • Run a HiveMQ broker in Docker and connect it to HiveMQ Platform.

  • Stream simulated sensor data through the broker.

  • Add the simulated data to a namespace.

  • Check the data health of your broker in the Analyze dashboard.

1. Create a New HiveMQ Account

First, navigate to hivemq.com.

On the HiveMQ homepage, click Try the platform and follow the online prompts to create your account:

  1. In the Explore HiveMQ for free dialog, select a login method.
    You can sign up with your GitHub, Google, or LinkedIn account, or with your email address.
    In this guide, we use the email option. After you enter your email address, click Continue.

  2. HiveMQ sends an OTP (One-Time Password) code to the email address you provided. Copy and paste the OTP to the Verify your email dialog, and click Verify email to continue.

  3. In the Create your account dialog, enter a password and click Create account.

  4. To complete your sign-up, enter basic contact details for your user profile and click Continue.

HiveMQ creates your account, uses the company name that you provided to create an Organization, and assigns your account an owner role in the HiveMQ Platform.

The Explore page

After you create your account, HiveMQ Platform opens the Explore page. The Getting started card lists four tasks and tracks your progress:

  • Connect a broker

  • Start streaming data

  • Discover ungoverned traffic and create a namespace

  • Deploy an agent

You can return to the Explore page at any time to see which tasks are complete.

2. Add a HiveMQ Enterprise MQTT Broker

Next, get HiveMQ running on your infrastructure so that you can stream data to the platform:

  1. On the Getting started section of the Explore page, click Get a HiveMQ Broker.

  2. On the Choose how to run HiveMQ page, select the HiveMQ Software card and click Continue.

  3. On the How to deploy your broker page, select Docker. The page lists several ways to run a self-managed HiveMQ broker. This guide uses Docker.

  4. In the Your license section, review the license that HiveMQ assigned to your broker. HiveMQ creates a license with a random name and the Lab package. The license shows the status Pending deployment until your broker connects. To use a different license, select it from the list.

  5. In the Run your broker section, click the copy icon next to the command. The command sets your license key as an environment variable and starts the broker. You do not need to edit it.

  6. Open a terminal window and run the command you copied. Wait until your HiveMQ broker is up and running. Select View broker to continue.

  7. On the page for your new broker, confirm that the Broker connected! notice appears.

  8. In the Configuration section, confirm that the Data Intelligence status is Connected.

  9. (Optional) In the Cluster name field, enter a name for your broker. Each broker deployment forms a cluster, so this field sets the name of both.

  10. On the Broker connected banner, click Next, get data flowing to continue.

3. Stream test data

Now that your broker is connected, publish simulated sensor data to start streaming data into the platform. You can also connect your own devices instead.

  1. In the Get data flowing section, select the source of your data. In this guide, we use the Use simulated data option.

  2. To publish a stream of simulated sensor readings to your Docker broker, leave your Docker broker running and copy the command shown for Use simulated data.

  3. Open another terminal window and run the command that you copied.

  4. On the page for your broker, confirm that the Data is flowing! notice appears.

  5. Click Next, govern your data to continue.

4. Organize your data into a namespace

Once data is flowing through your connected broker, you can use the data intelligence capabilities of the Contextualize layer to give it meaning.

  1. On the Contextualize Data page, click Discovery to see the ungoverned MQTT traffic that is already flowing through your broker. These are the MQTT topics that the broker has detected but that no namespace covers yet.

  2. On the Discover your ungoverned traffic page, click Next to start a tour of the discovery workflow. The Ungoverned data panel shows a list of all discovered topics.

  3. On the Select Topics to Add to Your Namespace page, choose the topics in the Ungoverned data list that you want to govern.

  4. Click Approve into namespace to add the selected topics to your namespace and continue.

  5. On the Namespace page, select the name of your broker and click Activate <#> items. The platform governs all data that flows through the nodes you activate. A notification banner confirms that the approved topics are now in your namespace.

The Unified Namespace (UNS) you created defines which topics exist, how payloads are structured, and which data types are expected.
You can refine your namespace at any time. For more information, see What is a Unified Namespace.

5. Check the health of your data

The platform continuously compares the live traffic from your connected brokers against your namespace definitions. In this step, you review the results to detect patterns and generate insights.

  1. In the top navigation, select Analyze. The Data Health dashboard opens. Here, you get a real-time overview of how well your live MQTT traffic aligns with the namespace definitions you created in Contextualize. The platform provides detailed metrics for data health in total and per broker that let you verify whether the data your broker is receiving is reliable.

  2. Switch to the Deviations tab on Analyze to see if any of your governed traffic fails to match its namespace definition. Each connected broker detects deviations locally and reports them to the platform.

  3. Click a deviation to inspect its details and decide what action to take.

The simulated data script generates deviations to help you understand how the Data Health feature works.

Next steps

You now have connected, contextualized, and analyzed data. The last layer of the platform is Act: AI agents that observe your governed data, reason over it, and take actions that your team approves.

HiveMQ Agentic AI for operations is in public preview.

  • To learn more about agents, click Act in the top navigation. On the Act page, click See how it works to follow an introductory tour.