Orchestrate Fabric Data workloads with Airflow

With so many different Fabric items to work with that allow you to move and transform data, it becomes essential to have a way to “arrange” all that movement of data. Enter Apache Airflow, now available as it’s own integrated item in Fabric.

An Airflow job will allow you to define the different steps your entire load process for your warehouse needs to go through and in which order. You model these steps in a Directed Acyclis Graph (DAG). I came across this nice explanation of this concept – https://www.astronomer.io/docs/learn/dags/

At the end of the day, you’ll have a robust definition of the steps, but also the ability to follow in real-time the status of the different nodes, compare metrics with previous runs, have log files with the nitty-gritty detail and even link back into the Fabric item.

This item is still in preview, but it has all the hallmarks of becomng an essential tool to complete Fabric from an orchestration point of view. You could claim that pipelines can do the same, but you’ll quickly lose the overview of pipelines calling pipelines in a more complex environment.

I wanted to provide all the steps to run your first DAG in Fabric, documenting the different challenges and technical specifics I had to overcome.

Permissions

A few settings need to be taken into account to make sure all of the next steps can be executed.

Fabric Tenant Admin

In the Fabric admin tenant settings, you’ll have to enable the Airflow preview for now. This is disabled by default.

Also, make sure that you have enabled the access for service principals. If not, you cannot assign membership to the workspace to a Service Principal.

Authentication

This for sure is again the most finnicky and tedious part to get right. Given that Airflow is not build as a fully integrated part of Fabric, it inherently has to deal with its own connections and security.

EntraID Admin Center

In Entra admin center, go to Conset and permissions : Consent and permissions – Microsoft Entra admin center

Select “Allow user consent for apps”. I was also able to use the second option for the DAG with Fabric items I was executing, but this is how it’s specified in the Microsoft documentation.

Service Principal

In the Azure portal, in EntraID, you’ll need to create an App Registration. You can follow the instructions in the Microsoft documentation.

The important steps are:

Name : anything, e.g. AirFlow. Note down the Client ID (application ID) from the overview page.
In Authentication, add a Platform, web link, with the Redirect URI set to https://login.microsoftonline.com/common/oauth2/nativeclient
In Certificates & secrets, add a secret and store it safely
In API Permissions, add following permissions from Power BI Service and Microsoft Graph

(add an Owner to the service principal, just so you can delegate the maintenance, not essential for this setup)

Refresh Token

Finally, we’ll be able to get a refresh token using the OAuth2 auth code flow protocol which will be the final piece of the puzzle to use a Fabric Airflow DAG connection.

Get Code

I tend to use Postman for this, due to its advanced configuration options.

A first call will allow us to get a code, with which in the second request we can retrieve a refresh token.

Prepare a GET request to this URL : https://login.microsoftonline.com/{tenant-id}/oauth2/v2.0/authorize where you replace tenant id with the value of your Fabric tenant, which you can find in the Fabric portal, ? menu, About PowerBI. There will be a line with Tenant URL, which contains the tenant id in the ctid parameter.

Provide the following parameters:

client_id : from the service principal defined earlier
response_type : code
redirect_uri : https://login.microsoftonline.com/common/oauth2/nativeclient
response_mode : query
state : 12345 (this is just meant as a check in the protocol, the same field is returned with the same value)
scope : https://api.fabric.microsoft.com/Item.Execute.All https://api.fabric.microsoft.com/Item.ReadWrite.All offline_access openid profile
client_secret : the secret created in the service principal defined earlier

You’ll get a URL that looks like this:

https://login.microsoftonline.com/xxxxxxxxxxxxxxx/oauth2/v2.0/authorize?client_id=xxxxxxxxxxxxxxxxxx&response_type=code&redirect_uri=https://login.microsoftonline.com/common/oauth2/nativeclient&response_mode=query&state=12345&scope=https://api.fabric.microsoft.com/Item.Execute.All https://api.fabric.microsoft.com/Item.ReadWrite.All offline_access openid profile&client_secret=xxxxxxxxxxxxxx

Paste this in your browser and authenticate with your account. The browser URL will now be replaced with a new URL:

https://login.microsoftonline.com/common/oauth2/nativeclient?code=1.AQwA60ocEiofyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy-yyyyyyyyyyyyy0QBqn3mg&state=12345&session_state=aefe425d-yyyyyyyyyyyyy-88143d8d206e

The field of interest is the code field. Save this value.
Note that you only have to do this once, going forward, the refresh token will be reused for any connection made in Airflow.

Get Refresh Token

Using Postman, you can now create a second request. This time it’s a POST request to the URL https://login.microsoftonline.com/{tenant-id}/oauth2/v2.0/token

Provide the following data in the body (form-data works well in Postman):

client_id : same as above
client_secret : same as above
grant_type : authorization_code
code : the code returned above
redirect_url : https://login.microsoftonline.com/common/oauth2/nativeclient
scope : https://api.fabric.microsoft.com/Item.Execute.All https://api.fabric.microsoft.com/Item.ReadWrite.All offline_access openid profile

Send the request and you’ll normally get a status 200 back with in the Body the “refresh_token”, amongst others.

Airflow setup

Finally, we can create a new Airflow item in Fabric. You’ll find yourself in an empty editor.

Create Connection for Fabric

On the top you’ll find “View Apache Airflow Connectors”. Click on it to create a new connector.

Make sure to fill in

Connection ID : give it a meaningfull name, you’ll refer to it in code that uses this connection
Connection Type : Generic
Login : the client ID from before
Password : the Refresh Token from before
Extra : the following block :
{
“tenantId”: “xxxxxxxxxxx”,
“clientSecret”: “yyyyyyyyyyyyyyyyyyy”,
“scopes”: “https://api.fabric.microsoft.com/Item.Execute.All https://api.fabric.microsoft.com/Item.ReadWrite.All offline_access openid profile”
}

Don’t make the mistake to specify client_secret, that was mentioned incorrectly in various fora.

Create Connection for PowerBI

Unfortunately, a separate connection for a PowerBI task is needed as they differ ever so slightly.

Make sure to fill in

Connection ID : give it a meaningfull name, you’ll refer to it in code that uses this connection
Connection Type : Generic
Login : the client ID from before
Password : the client secret
Extra : the following block :
{
“tenantId”: “xxxxxxxxxxx”
}

Airflow settings

In Settings (the cog on the top left), make sure to include airflow-powerbi-plugin – this is only needed to run the PowerBI Refresh step.

Also check the “Enable triggerers”, as this will allow you to include a plugin to link from your running DAG to the fabric item.

Create DAG to load the DW

When in the editor you can click “+ New” in the Explorer. Select dags folder and create sales_load_to_dw.py

This will create a boilerplate code for a first “Hello World” DAG. You can replace the code with the below, which is a DAG that calls 2 Pipelines, then runs 2 Notebook and afterwards Refreshes a semantic model. It simulates ingesting data from 2 different sources in Bronze, then performing the load to Silver using a notebook and to Gold with another notebook. Finally it will refresh the related semantic model in PowerBI.

from airflow import DAG
from datetime import datetime
from apache_airflow_microsoft_fabric_plugin.operators.fabric import FabricRunItemOperator
from airflow_powerbi_plugin.operators.powerbi import PowerBIDatasetRefreshOperator
from airflow.hooks.base_hook import BaseHook

workspace_id="<your workspace id>"

with DAG(
    dag_id="Load_DW",
    schedule_interval=None,
    start_date=datetime(2024, 11, 1),
    catchup=False,
    concurrency=20,
) as dag:

    ingest_nav_to_bronze = FabricRunItemOperator(
        task_id="task_ingest_nav_to_bronze",
        fabric_conn_id="fabric",
        workspace_id=workspace_id,
        item_id="<your pipeline id>",
        job_type="Pipeline",
        wait_for_termination=True,
        deferrable=False,
    )

    ingest_bc_to_bronze = FabricRunItemOperator(
        task_id="task_ingest_bc_to_bronze",
        fabric_conn_id="fabric",
        workspace_id=workspace_id,
        item_id="<your pipeline id>",
        job_type="Pipeline",
        wait_for_termination=True,
        deferrable=False,
    )

    load_erp_to_silver = FabricRunItemOperator(
        task_id="task_load_erp_to_silver",
        fabric_conn_id="fabric",
        workspace_id=workspace_id,
        item_id="<your notebook id>",
        job_type="RunNotebook",
        wait_for_termination=True,
        deferrable=False,
    )

    load_gold = FabricRunItemOperator(
        task_id="task_load_gold",
        fabric_conn_id="fabric",
        workspace_id=workspace_id,
        item_id="<your notebook id>",
        job_type="RunNotebook",
        wait_for_termination=True,
        deferrable=False,
    )
    
    refresh_pbi_sales = PowerBIDatasetRefreshOperator(
       powerbi_conn_id= "powerbi",
       task_id="task_refresh_pbi_sales",
       dataset_id="<your dataset id>",
       group_id=workspace_id,
    )

    ingest_nav_to_bronze>>load_erp_to_silver
    ingest_bc_to_bronze>>load_erp_to_silver>>load_gold>>refresh_pbi_sales

Create plugin to monitor Fabric

In order to get an option to jump to the Fabric item execution details, you can add a plugin file by clicking “+ New” and select the plugin folder. Create a file fabric_hook.py with the below content:

from airflow.plugins_manager import AirflowPlugin
from apache_airflow_microsoft_fabric_plugin.hooks.fabric import FabricHook
from apache_airflow_microsoft_fabric_plugin.operators.fabric import FabricRunItemLink

class AirflowFabricPlugin(AirflowPlugin):
    name = "fabric_plugin"
    operator_extra_links = [FabricRunItemLink()]
    hooks = [FabricHook]

Create plugin to monitor PowerBI

Similar to the above create a plugin file for powerbi named powerbi_hook.py with below content:

from airflow.plugins_manager import AirflowPlugin

from airflow_powerbi_plugin.hooks.powerbi import PowerBIHook
from airflow_powerbi_plugin.operators.powerbi import PowerBILink

# Defining the plugin class
class AirflowExtraLinkPlugin(AirflowPlugin):
    """
    PowerBI plugin.
    """

    name = "powerbi_plugin"
    operator_extra_links = [
        PowerBILink(),
    ]
    hooks= [
        PowerBIHook,
    ]

Airflow DAG execution

Finally all pieces are in place. Now you can run the DAG and if all is configured correctly the graph will be executed step by step as designed.

The execution can be monitorred with the “Monitor in Apache Airflow” button, providing detailed insight in the progress.

You can view the DAG as a graph (or grid) like below.

Also the past execution statuses can be monitorred and comparisons with execution duration can be done. Clicking on a square brings you to the details and logs of the specific node.

Thanks to the plugin hooks you’ll see a button in Extra links “Monitor Item Run” (or “Monitor PowerBI dataset”), which brings you to the Fabric/PowerBI item with logs.

Conclusion

With the above setup you can monitor the Fabric items and datasets from one single orchestration tool. I hope my article opens up this great technology for you to use data transformations and a full ETL/ELT flow in a professional way in the Fabric environment.

Mattias De Smet

Orchestrate Fabric Data workloads with Airflow

Permissions

Fabric Tenant Admin

Authentication

EntraID Admin Center

Service Principal

Refresh Token

Get Code

Get Refresh Token

Airflow setup

Create Connection for Fabric

Create Connection for PowerBI

Airflow settings

Create DAG to load the DW

Create plugin to monitor Fabric

Create plugin to monitor PowerBI

Airflow DAG execution

Conclusion

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Orchestrate Fabric Data workloads with Airflow

Permissions

Fabric Tenant Admin

Authentication

EntraID Admin Center

Service Principal

Refresh Token

Get Code

Get Refresh Token

Airflow setup

Create Connection for Fabric

Create Connection for PowerBI

Airflow settings

Create DAG to load the DW

Create plugin to monitor Fabric

Create plugin to monitor PowerBI

Airflow DAG execution

Conclusion

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