Airflow

In this section, we provide guides and references to use the Airflow connector.

Configure and schedule Airflow metadata workflow from the OpenMetadata UI:

If you don't want to use the OpenMetadata Ingestion container to configure the workflows via the UI, then you can check the following docs to extract metadata directly from your Airflow instance or via the CLI:

Requirements

To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with custom Airflow plugins to handle the workflow deployment.

Metadata Ingestion

1. Visit the Services Page

The first step is ingesting the metadata from your sources. Under Settings, you will find a Services link an external source system to OpenMetadata. Once a service is created, it can be used to configure metadata, usage, and profiler workflows.

To visit the Services page, select Services from the Settings menu.

Find Services under the Settings menu

2. Create a New Service

Click on the Add New Service button to start the Service creation.

Add a new Service from the Services page

3. Select the Service Type

Select Airflow as the service type and click Next.

Select your service from the list

4. Name and Describe your Service

Provide a name and description for your service as illustrated below.

Service Name

OpenMetadata uniquely identifies services by their Service Name. Provide a name that distinguishes your deployment from other services, including the other {connector} services that you might be ingesting metadata from.

Provide a Name and description for your Service

5. Configure the Service Connection

In this step, we will configure the connection settings required for this connector. Please follow the instructions below to ensure that you've configured the connector to read from your airflow service as desired.

Configure the service connection by filling the form

Once the credentials have been added, click on Test Connection and Save the changes.

Test the connection and save the Service

Connection Options

• Host and Port: URL to the Airflow instance.
• Number of Status: Number of status we want to look back to in every ingestion (e.g., Past executions from a DAG).
• Connection: Airflow metadata database connection. See these docs for supported backends.

In terms of connection we support the following selections:

• backend: Should not be used from the UI. This is only applicable when ingesting Airflow metadata locally by running the ingestion from a DAG. It will use the current Airflow SQLAlchemy connection to extract the data.
• MySQL, Postgres, MSSQL and SQLite: Pass the required credentials to reach out each of these services. We will create a connection to the pointed database and read Airflow data from there.

6. Configure Metadata Ingestion

In this step we will configure the metadata ingestion pipeline, Please follow the instructions below

Configure Metadata Ingestion Page

Metadata Ingestion Options

• Name: This field refers to the name of ingestion pipeline, you can customize the name or use the generated name.
• Pipeline Filter Pattern (Optional): Use to pipeline filter patterns to control whether or not to include pipeline as part of metadata ingestion.
  • Include: Explicitly include pipeline by adding a list of comma-separated regular expressions to the Include field. OpenMetadata will include all pipeline with names matching one or more of the supplied regular expressions. All other schemas will be excluded.
  • Exclude: Explicitly exclude pipeline by adding a list of comma-separated regular expressions to the Exclude field. OpenMetadata will exclude all pipeline with names matching one or more of the supplied regular expressions. All other schemas will be included.
• Include lineage (toggle): Set the Include lineage toggle to control whether or not to include lineage between pipelines and data sources as part of metadata ingestion.
• Enable Debug Log (toggle): Set the Enable Debug Log toggle to set the default log level to debug, these logs can be viewed later in Airflow.

7. Schedule the Ingestion and Deploy

Scheduling can be set up at an hourly, daily, or weekly cadence. The timezone is in UTC. Select a Start Date to schedule for ingestion. It is optional to add an End Date.

Review your configuration settings. If they match what you intended, click Deploy to create the service and schedule metadata ingestion.

If something doesn't look right, click the Back button to return to the appropriate step and change the settings as needed.

Schedule the Ingestion Pipeline and Deploy

After configuring the workflow, you can click on Deploy to create the pipeline.

8. View the Ingestion Pipeline

Once the workflow has been successfully deployed, you can view the Ingestion Pipeline running from the Service Page.

View the Ingestion Pipeline from the Service Page

9. Workflow Deployment Error

If there were any errors during the workflow deployment process, the Ingestion Pipeline Entity will still be created, but no workflow will be present in the Ingestion container.

You can then edit the Ingestion Pipeline and Deploy it again.

Edit and Deploy the Ingestion Pipeline

From the Connection tab, you can also Edit the Service if needed.