Visualize data from Azure Data Explorer in Grafana

Grafana is an analytics platform that enables you to query and visualize data, then create and share dashboards based on your visualizations. Grafana provides an Azure Data Explorer plugin, which enables you to connect to and visualize data from Azure Data Explorer. In this article, you learn to set up Azure Data Explorer as a data source for Grafana, and then visualize data from a sample cluster.

Use the following video, to learn how to use Grafana's Azure Data Explorer plugin, set up Azure Data Explorer as a data source for Grafana, and then visualize data.

Instead you can configure the data source and visualize data as detailed in the article below.


The StormEvents sample data set contains weather-related data from the National Centers for Environmental Information.

Configure the data source

You perform the following steps to configure Azure Data Explorer as a data source for your dashboard tool. We'll cover these steps in more detail in this section:

  1. Create an Azure Active Directory (Azure AD) service principal. The service principal is used by your dashboard tool to access the Azure Data Explorer service.

  2. Add the Azure AD service principal to the viewers role in the Azure Data Explorer database.

  3. Specify your dashboard tool connection properties based on information from the Azure AD service principal, then test the connection.

Create a service principal

You can create the service principal in the Azure portal or using the Azure CLI command-line experience. Regardless of which method you use, after creation you get values for four connection properties that you'll use in later steps.

Azure portal

  1. To create the service principal, follow the instructions in the Azure portal documentation.

    1. In the Assign the application to a role section, assign a role type of Reader to your Azure Data Explorer cluster.

    2. In the Get values for signing in section, copy the three property values covered in the steps: Directory ID (tenant ID), Application ID, and Password.

  2. In the Azure portal, select Subscriptions then copy the ID for the subscription in which you created the service principal.

    Subscription ID - portal.

Azure CLI

  1. Create a service principal. Set an appropriate scope and a role type of reader.

    az ad sp create-for-rbac --name "https://{UrlToYourDashboard}:{PortNumber}" --role "reader" \
                             --scopes /subscriptions/{SubID}/resourceGroups/{ResourceGroupName}

    For more information, see Create an Azure service principal with Azure CLI.

  2. The command returns a result set like the following. Copy the three property values: appID, password, and tenant.

      "displayName": "{UrlToYourDashboard}:{PortNumber}",
      "name": "https://{UrlToYourDashboard}:{PortNumber}",
  3. Get a list of your subscriptions.

    az account list --output table

    Copy the appropriate subscription ID.

    Subscription ID - CLI.

Add the service principal to the viewers role

Now that you have a service principal, you add it to the viewers role in the Azure Data Explorer database. You can perform this task under Permissions in the Azure portal, or under Query by using a management command.

Azure portal - Permissions

  1. In the Azure portal, go to your Azure Data Explorer cluster.

  2. In the Overview section, select the database with the StormEvents sample data.

    Select database.

  3. Select Permissions then Add.

    Database permissions.

  4. Under Add database permissions, select the Viewer role then Select principals.

    Add database permissions.

  5. Search for the service principal you created. Select the principal, then Select.

    Screenshot of the Azure portal New Principals pane. The Select button and two fields with indecipherable service principal properties are highlighted.

  6. Select Save.

    Screenshot of the Add Database Permissions pane in the Azure portal. The Save button is highlighted.

Management command - Query

  1. In the Azure portal, go to your Azure Data Explorer cluster, and select Query.

    Screenshot of an Azure Data Explorer cluster in the Azure portal. The Query item is highlighted.

  2. Run the following command in the query window. Use the application ID and tenant ID from the Azure portal or CLI.

    .add database {TestDatabase} viewers ('aadapp={ApplicationID};{TenantID}')

    The command returns a result set like the following. In this example, the first row is for an existing user in the database, and the second row is for the service principal that was just added.

    Result set.

Specify properties and test the connection

With the service principal assigned to the viewers role, you now specify properties in your instance of Grafana, and test the connection to Azure Data Explorer.

  1. In Grafana, on the left menu, select the gear icon then Data Sources.

    Data sources.

  2. Select Add data source.

  3. On the Data Sources / New page, enter a name for the data source, then select the type Azure Data Explorer Datasource.

    Connection name and type.

  4. In Settings > Connection details, enter the name of your cluster in the form https://{ClusterName}.{Region} Enter the other values from the Azure portal or CLI. See the table below the following image for a mapping.

    Connection properties.

    Grafana UI Azure portal Azure CLI
    Subscription Id SUBSCRIPTION ID SubscriptionId
    Tenant Id Directory ID tenant
    Client Id Application ID appId
    Client secret Password password
  5. Select Save & Test.

    If the test is successful, go to the next section. If you come across any issues, check the values you specified in Grafana, and review previous steps.

Optimize queries

There are two features that can be used for query optimization:

To perform the optimization, in Data Sources > Settings > Query Optimizations, make the needed changes.

Query optimization pane.

Optimize dashboard query rendering performance using query results caching

When a dashboard or visual is rendered more than once by one or more users, Grafana, by default, sends at least one query to Azure Data Explorer. Enable Query results caching to improve dashboard rendering performance and reduce load on the Azure Data Explorer cluster. During the specified time range, Azure Data Explorer will use the results cache to retrieve the previous results and won't run an unnecessary query. This capability is especially effective in reducing load on resources and improving performance when multiple users are using the same dashboard.

To enable results cache rendering, do the following in the Query Optimizations pane:

  1. Disable Use dynamic caching.
  2. In Cache Max Age, enter the number of minutes during which you want to use cached results.

Enable weak consistency

Clusters are configured with strong consistency. This guarantees that query results are up to date with all changes in the cluster. When enabling weak consistency, query results can have a 1-2 minutes lag following cluster alterations. On the other hand, weak consistency may boost visual rendering time. Therefore if immediate consistency isn't critical and performance is marginal, enable weak consistency to improve performance. For more information on query consistency, see Query consistency.

To enable weak consistency, in the Query Optimizations pane > Data consistency, select Weak.

Visualize data

Now you've finished configuring Azure Data Explorer as a data source for Grafana, it's time to visualize data. We'll show a basic example using both the query builder mode and the raw mode of the query editor. We recommend looking at Write queries for Azure Data Explorer for examples of other queries to run against the sample data set.

  1. In Grafana, on the left menu, select the plus icon then Dashboard.

    Create dashboard.

  2. Under the Add tab, select Add new panel.

    Add graph.

  3. On the graph panel, select Panel Title then Edit.

    Edit panel.

  4. At the bottom of the panel, select Data Source then select the data source that you configured.

    Select data source.

Query builder mode

The query editor has two modes. The query builder mode and raw mode. Use the query builder mode to define your query.

  1. Below the data source, select Database and choose your database from the drop-down.

  2. Select From and choose your table from the drop-down.

    Select table in query builder.

  3. Once the table is defined, filter the data, select the values to present, and define the grouping of those values.


    1. Click + to right of Where (filter) to select from the drop-down one or more columns in your table.
    2. For each filter, define the value(s) by using the applicable operator. This selection is similar to using the where operator in Kusto Query Language.

    Value selection

    1. Click + to right of value columns to select from the drop-down the value columns that will be displayed in the panel.
    2. For each value column, set the aggregation type. One or more value columns can be set. This selection is equivalent to using the summarize operator.

    Value grouping
    Click + to right of Group by (summarize) to select from the drop-down one or more columns that will be used to arrange the values into groups. This is equivalent to the group expression in the summarize operator.

  4. To execute the query, select Run query.

    Query builder with all values complete.


    While finalizing the settings in the query builder, a Kusto Query Language query is created. This query shows the logic you constructed with the graphical query editor.

  5. Select Edit KQL to move to raw mode and edit your query using the flexibility and power of the Kusto Query Language.

Query builder with raw query.

Raw mode

Use raw mode to edit your query.

  1. In the query pane, copy in the following query then select Run Query. The query buckets the count of events by day for the sample data set.

    | summarize event_count=count() by bin(StartTime, 1d)

    Run query.

  2. The graph doesn't show any results because it's scoped by default to data from the last six hours. On the top menu, select Last 6 hours.

    Last six hours.

  3. Specify a custom range that covers 2007, the year included in our StormEvents sample data set. Select Apply.

    Custom date range.

    Now the graph shows the data from 2007, bucketed by day.

    Finished graph.

  4. On the top menu, select the save icon: Save icon..


To switch to the query builder mode, select Switch to builder. Grafana will convert the query to the available logic in the Query builder. The query builder logic is limited and therefore you may lose manual changes done to the query.

Move to builder from raw mode.

Create Alerts

  1. In Home Dashboard, select Alerting > Notification channels to create a new notification channel

    create notification channel.

  2. Create a new Notification channel, then Save.

    Create new notification channel.

  3. On the Dashboard, select Edit from the dropdown.

    select edit in dashboard.

  4. Select the alert bell icon to open the Alert pane. Select Create Alert. Complete the following properties in the Alert pane.

    alert properties.

  5. Select the Save dashboard icon to save your changes.

Next steps