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Connect Azure Managed Grafana to the Reference Solution

You can use Azure Managed Grafana to create a dashboard on Azure for the solution described in this article. Use Grafana within manufacturing to create dashboards that display real-time data. The following steps show you how to enable Grafana on Azure and create a dashboard with the simulated production line data from Azure Data Explorer.

Architecture diagram of the reference solution

Enable the Azure Managed Grafana service

To create an Azure Managed Grafana service and configure it with permissions to access the ontologies database:

  1. In the Azure portal, search for Grafana, and then select the Azure Managed Grafana service.

  2. To create the service, on Create Grafana Workspace enter a name for your instance. Choose all the default options.

  3. After the service is created, make sure your Grafana instance has a system assigned managed identity. In the Azure portal, go to the Identity blade of your Azure Managed Grafana instance. If the system assigned managed identity isn't enabled, enable it. Make a note of the Object (principal) ID value, you need it later.

  4. To grant permission for the managed identity to access the ontologies database in Azure Data Explorer:

    1. Go to the Permissions blade in your Azure Data Explorer instance in the Azure portal.
    2. Select Add > AllDatabasesViewer.
    3. Search for and select the Object (principal) ID value you noted previously.

Add a new data source in Grafana

Add a new data source to connect to Azure Data Explorer. In this sample, use a system assigned managed identity to connect to Azure Data Explorer. To configure the authentication, follow these steps:

To add the data source in Grafana, follow these steps:

  1. Go to the endpoint URL for your Grafana instance. You can find the endpoint URL in the Azure Managed Grafana page for your instance in the Azure portal. Then sign in to your Grafana instance.
  2. In the Grafana dashboard, select Connections > Data sources, and then select Add new data source. Scroll down and select Azure Data Explorer Datasource.
  3. Choose Managed Identity as the authentication menu. Then add the URL of your Azure Data Explorer cluster. You can find the URL in the Azure Data Explorer instance menu in the Azure portal under URI.
  4. Select Save and test to verify the datasource connection.

Import a sample dashboard

Now you're ready to import the sample dashboard.

  1. Download the Sample Grafana Manufacturing Dashboard dashboard.
  2. In the Grafana menu, go to Dashboards and then select New > Import.
  3. Select Upload dashboard JSON file and select the samplegrafanadashboard.json file that you downloaded previously. Select Import.
  4. On the OEE Station panel, select Edit and then select the Azure Data Explorer Data source you set up previously. Then select KQL in the query panel and add the following query: print round (CalculateOEEForStation('${Station}', '${Location}', '${CycleTime}', '${__from:date:iso}', '${__to:date:iso}') * 100, 2). Select Apply to apply your changes and go back to the dashboard.
  5. On the OEE Line panel, select Edit and then select the Azure Data Explorer Data source you set up previously. Then select KQL in the query panel and add the following query: print round(CalculateOEEForLine('${Location}', '${CycleTime}', '${__from:date:iso}', '${__to:date:iso}') * 100, 2). Select Apply to apply your changes and go back to the dashboard.
  6. On the Discarded products panel, select Edit and then select the Azure Data Explorer Data source you set up previously. Then select KQL in the query panel and add the following query: opcua_metadata_lkv| where Name contains '${Station}'| where Name contains '${Location}'| join kind=inner (opcua_telemetry| where Name == "NumberOfDiscardedProducts"| where Timestamp > todatetime('${__from:date:iso}') and Timestamp < todatetime('${__to:date:iso}')) on DataSetWriterID| extend numProd = toint(Value)| summarize max(numProd). Select Apply to apply your changes and go back to the dashboard.
  7. On the Manufactured products panel, select Edit and then select the Azure Data Explorer Data source you set up previously. Then select KQL in the query panel and add the following query: opcua_metadata_lkv| where Name contains '${Station}'| where Name contains '${Location}'| join kind=inner (opcua_telemetry| where Name == "NumberOfManufacturedProducts"| where Timestamp > todatetime('${__from:date:iso}') and Timestamp < todatetime('${__to:date:iso}')) on DataSetWriterID| extend numProd = toint(Value)| summarize max(numProd). Select Apply to apply your changes and go back to the dashboard.
  8. On the Energy Consumption panel, select Edit and then select the Azure Data Explorer Data source you set up previously. Then select KQL in the query panel and add the following query: opcua_metadata_lkv| where Name contains '${Station}'| where Name contains '${Location}'| join kind=inner (opcua_telemetry | where Name == "Pressure" | where Timestamp > todatetime('${__from:date:iso}') and Timestamp < todatetime('${__to:date:iso}')) on DataSetWriterID| extend energy = todouble(Value)| summarize avg(energy)); print round(toscalar(averageEnergyConsumption) * 1000, 2). Select Apply to apply your changes and go back to the dashboard.
  9. On the Pressure panel, select Edit and then select the Azure Data Explorer Data source you set up previously. Then select KQL in the query panel and add the following query: opcua_metadata_lkv| where Name contains '${Station}'| where Name contains '${Location}'| join kind=inner (opcua_telemetry | where Name == "Pressure" | where Timestamp > todatetime('${__from:date:iso}') and Timestamp < todatetime('${__to:date:iso}')) on DataSetWriterID| extend NodeValue = toint(Value)| project Timestamp1, NodeValue. Select Apply to apply your changes and go back to the dashboard.

Configure alerts

In Grafana, you can also create alerts. In this example, you create a low OEE alert for one of the production lines.

  1. In the Grafana menu, go to Alerting > Alert rules.

  2. Select New alert rule.

  3. Enter a name for your alert, and select Azure Data Explorer as the data source. In the Define query and alert condition pane, select KQL.

  4. In the query field, enter the following query. This example uses the Seattle production line:

    let oee = CalculateOEEForStation("assembly", "seattle", 10000, now(), now(-1h));
print round(oee * 100, 2)

  5. Select Set as alert condition.

  6. Scroll down to the Expressions section. Delete the Reduce expression, you don't need it.

  7. For the alert threshold, select A as Input. Select IS BELOW and enter 10.

  8. Scroll down to the Set evaluation behavior section. Create a new Folder to save your alerts. Create a new Evaluation group and specify 2m.

  9. Select the Save rule and exit button in the upper right.

In the overview of your alerts, you can now see that an alert is triggered when your OEE is less than 10.