Comment on page


This example demonstrates how to use this Action Agent to manually trigger an Azure Data Factory Pipeline run.
Refer to configuration to understand all configuration options of this Agent.

Step 1: Add the Agent

Drag the Azure Data Factory Action Agent onto the canvas and rename the Agent. Link the input endpoint to the Calculated Field Agent (Add Parameters), the output to the printer, and save the Data Stream.

Step 2: Configure General

Select the Agent and click Configure. Keep the default Collection.

Step 3: Configure Authentication

Enter the authentication values: Subscription Id, Tenant Id, Client Id, and Client Secret.
You can untick Use Variables if you prefer to enter the values manually.

Step 4: Configure Data Factory

Select the resource group that contains the Azure Data Factory. The Data Factory dropdown will be populated with the Azure Data Factory instances present in the Resource Group.
Select the Azure Data Factory instance that contains the Pipeline to run. The Pipeline dropdown will be populated with all the published Pipelines present in the Azure Data Factory instance.
Select the Pipeline.

Step 5: Configure Pipeline Details

The grid is auto-populated with the list of parameters configured on the pipeline. Map each parameter to a column or attribute from the input payload.
This step can be skipped if there are no parameters.

Step 6: Results

Apply the changes and save the Data Stream.
Publish the Data Stream and let's look at the Live Data View. Observe the file data printed with the Pipeline Run Id appended. This Id can be used to check the status of the Pipeline Run in Azure Data Factory Studio.
Finally, inspect the Pipeline runs in Azure Data Factory Studio and use the ID to check the status. Observe that the pipeline was triggered and that it succeeded.


Security Key
Data Stream
Azure Data Factory Example.xuc
See the Import, Export, and Clone - XMPro article for steps to import a Data Stream.