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The Azure IoT explorer is a graphical tool for interacting with and devices connected to your IoT hub. This article focuses on using the tool to test your IoT Plug and Play devices. After installing the tool on your local machine, you can use it to connect to a hub. You can use the tool to view the telemetry the devices are sending, work with device properties, and invoke commands.

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This article shows you how to:

  • Install and configure the Azure IoT explorer tool.
  • Use the tool to interact with and test your IoT Plug and Play devices.

For more general information about using the tool, see the GitHub readme.

To use the Azure IoT explorer tool, you need:

Explorer
  • An Azure IoT hub. There are many ways to add an IoT hub to your Azure subscription, such as Creating an IoT hub by using the Azure CLI. You need the IoT hub connection string to run the Azure IoT explorer tool. If you don't have an Azure subscription, create a free account before you begin.
  • A device registered in your IoT hub. You can use IoT Explorer to create and manage device registrations in your IoT Hub.

Install Azure IoT explorer

Go to Azure IoT explorer releases and expand the list of assets for the most recent release. Download and install the most recent version of the application.

Important

Update to version 0.13.x to resolve models from any repository based on https://github.com/Azure/iot-plugandplay-models

Use Azure IoT explorer

For a device, you can either connect your own device, or use one of the sample simulated devices. For some example simulated devices written in different languages, see the Connect a sample IoT Plug and Play device application to IoT Hub quickstart.

Connect to your hub

The first time you run Azure IoT explorer, you're prompted for your IoT hub's connection string. After you add the connection string, select Connect. You can use the tool's settings to switch to another IoT hub by updating the connection string.

The model definition for an IoT Plug and Play device is stored in either the public repository, the connected device, or a local folder. By default, the tool looks for your model definition in the public repository and your connected device. You can add and remove sources, or configure the priority of the sources in Settings:

To add a source:

  1. Go to Home/IoT Plug and Play Settings
  2. Select Add and choose your source, from a repository or local folder.

To remove a source:

  1. Go to Home/IoT Plug and Play Settings
  2. Find the source you want to remove.
  3. Select X to remove it.

Change the source priorities:

Lake

You can drag and drop one of the model definition sources to a different ranking in the list.

View devices

After the tool connects to your IoT hub, it displays the Devices list page that lists the device identities registered with your IoT hub. You can select any entry in the list to see more information.

On the Devices list page you can:

  • Select New to register a new device with your hub. Then enter a device ID. Use the default settings to automatically generate authentication keys and enable the connection to your hub.
  • Select a device and then select Delete to delete a device identity. Review the device details before you complete this action to be sure you're deleting the right device identity.
Explorer

Interact with a device

On the Devices list page, select a value in the Device ID column to view the detail page for the registered device. For each device there are two sections: Device and Digital Twin.

Device

This section includes the Device Identity, Device Twin, Telemetry, Direct method, Cloud-to-device message, Module Identity tabs.

  • You can view and update the device identity information on the Device identity tab.
  • You can access the device twin information on the Device Twin tab.
  • If a device is connected and actively sending data, you can view the telemetry on the Telemetry tab.
  • You can call a direct method on the device on the Direct method tab.
  • You can send a cloud-to-device message on the Cloud-to-device messages tab.
  • You can access the module twin information.

IoT Plug and Play components

If the device is connected to the hub using a Model ID, the tool shows the IoT Plug and Play components tab where you can see the Model ID.

If the Model ID is available in one of the configured sources - Public Repo or Local Folder, the list of components is displayed. Selecting a component shows the properties, commands, and telemetry available.

On the Component page, you can view the read-only properties, update writable properties, invoke commands, and see the telemetry messages produced by this component.

Properties

You can view the read-only properties defined in an interface on the Properties (read-only) tab. You can update the writable properties defined in an interface on the Properties (writable) tab:

  1. Go to the Properties (writable) tab.
  2. Click the property you'd like to update.
  3. Enter the new value for the property.
  4. Preview the payload to be sent to the device.
  5. Submit the change.

After you submit a change, you can track the update status: synching, success, or error. When the synching is complete, you see the new value of your property in the Reported Property column. If you navigate to other pages before the synching completes, the tool still notifies you when the update is complete. You can also use the tool's notification center to see the notification history.

Commands

To send a command to a device, go to the Commands tab:

  1. In the list of commands, expand the command you want to trigger.
  2. Enter any required values for the command.
  3. Preview the payload to be sent to the device.
  4. Submit the command.

Telemetry

To view the telemetry for the selected interface, go to its Telemetry tab.

Known Issues

For a list of the IoT features supported by the latest version of the tool, see Feature list.

Next steps

In this how-to article, you learned how to install and use Azure IoT explorer to interact with your IoT Plug and Play devices. A suggested next step is to learn how to Install and use the DTDL authoring tools.

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Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. It helps you handle the many data streams emitted by modern software, so you can collect, store, and analyze data. Azure Data Explorer is ideal for analyzing large volumes of diverse data from any data source, such as websites, applications, IoT devices, and more. This data is used for diagnostics, monitoring, reporting, machine learning, and additional analytics capabilities. Azure Data Explorer makes it simple to ingest this data and enables you to do complex ad hoc queries on the data in seconds.

What makes Azure Data Explorer unique?

  • Scales quickly to terabytes of data, in minutes, allowing rapid iterations of data exploration to discover relevant insights.

  • Offers an innovative query language, optimized for high-performance data analytics.

  • Supports analysis of high volumes of heterogeneous data (structured and unstructured).

  • Provides the ability to build and deploy exactly what you need by combining with other services to supply an encompassing, powerful, and interactive data analytics solution.

Data warehousing workflow

Azure Data Explorer integrates with other major services to provide an end-to-end solution that includes data collection, ingestion, storage, indexing, querying, and visualization. It has a pivotal role in the data warehousing flow by executing the EXPLORE step of the flow on terabytes of diverse raw data.

Azure Data Explorer supports several ingestion methods, including connectors to common services like Event Hub, programmatic ingestion using SDKs, such as .NET and Python, and direct access to the engine for exploration purposes. Azure Data Explorer integrates with analytics and modeling services for additional analysis and visualization of data.

Azure Data Explorer flow

The following diagram shows the different aspects of working with Azure Data Explorer.

Work in Azure Data Explorer generally follows this pattern:

  1. Create database: Create a cluster and then create one or more databases in that cluster. Quickstart: Create an Azure Data Explorer cluster and database

  2. Ingest data: Load data into database tables so that you can run queries against it. Quickstart: Ingest data from Event Hub into Azure Data Explorer

  3. Query database: Use our web application to run, review, and share queries and results. It's available in the Azure portal and as a stand-alone application. You can also send queries programmatically (using an SDK) or to a REST API endpoint. Quickstart: Query data in Azure Data Explorer

Microsoft Azure Storage Explorer Download

Query experience

File

A query in Azure Data Explorer is a read-only request to process data and return the results of this processing, without modifying the data or metadata. You continue refining your queries until you've completed your analysis. Azure Data Explorer makes this process easy because of its fast ad hoc query experience.

Azure Data Explorer handles large amounts of structured, semi-structured (JSON-like nested types) and unstructured (free-text) data equally well. It allows you to search for specific text terms, locate particular events, and perform metric-style calculations on structured data. Azure Data Explorer bridges the worlds of unstructured text logs and structured numbers and dimensions by extracting values in runtime from free-form text fields. Data exploration is simplified by combining fast text indexing, column store, and time series operations.

Azure Data Explorer capabilities are extended by other services built on its powerful query language, including Azure Monitor logs, Application Insights, Time Series Insights, and Microsoft Defender for Endpoint.

How to provide feedback

We would be thrilled to hear your feedback about Azure Data Explorer and its query language at:

Microsoft Azure Explorer

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