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dbt Cloud

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Ingestion Deployment

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. If you want to install it manually in an already existing Airflow host, you can follow this guide.

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 run the Ingestion Framework in any orchestrator externally.

Requirements

dbt Cloud Versions

OpenMetadata is integrated with DBT cloud up to version 1.8 and will continue to work for future DBT cloud versions.

The Ingestion framework uses DBT Cloud APIs to connect to the dbtcloud and fetch metadata.

dbt Cloud Permissions

The DBT Clous API User token or Service account token must have the permission to fetch Metadata. To know more about permissions required refer here.

dbt Cloud Account

DBT Cloud multi-tenant or single tenant account is required.
You must be on a Team or Enterprise plan.
Your projects must be on dbt version 1.0 or later. Refer to Upgrade dbt version in Cloud to upgrade.

Metadata Ingestion

1. Visit the Services Page

The first step is to ingest the metadata from your sources. To do that, you first need to create a Service connection first.

This Service will be the bridge between OpenMetadata and your source system.

Once a Service is created, it can be used to configure your ingestion workflows.

Select your Service Type and Add a New Service

2. Create a New Service

Click on Add New Service to start the Service creation.

Add a new Service from the Services page

3. Select the Service Type

Select DBTCloud 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.

Service Name

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

Note that when the name is set, it cannot be changed.

Provide a Name and description for your Service

5. Configure the Service Connection

In this step, we will configure the connection settings required for DBTCloud.

Please follow the instructions below to properly configure the Service to read from your sources. You will also find helper documentation on the right-hand side panel in the UI.

Configure the Service connection by filling the form

Connection Details

Host: DBT cloud Access URL eg.https://abc12.us1.dbt.com. Go to your dbt cloud account settings then go to the Access URLs section. In there you will find various URLs we need the Access URL from that section as the Host. For more info visit here.
Discovery API URL : DBT cloud Discovery API URL eg. https://abc12.metadata.us1.dbt.com/graphql. Go to your dbt cloud account settings where you found your Access URL. In there scroll down to find Discovery API URL . If your Discovery API URL doesn't contain the /graphql at the end please add it. Make sure you have /graphql at the end of your URL. Note that Semantic Layer GraphQL API URL is different from Discovery API URL.
Account Id : The Account ID of your DBT cloud Project. Go to your dbt cloud account settings then in the Account information you will find Account ID. This will be a numeric value but in openmetadata we parse it as a string.
Job Id : Optional. The Job ID of your DBT cloud Job in your Project to fetch metadata for. Look for the segment after "jobs" in the URL. For instance, in a URL like https://cloud.getdbt.com/accounts/123/projects/87477/jobs/73659994, the job ID is 73659994. This will be a numeric value but in openmetadata we parse it as a string. If not passed all Jobs under the Account id will be ingested.
Token : The Authentication Token of your DBT cloud API Account. To get your access token you can follow the docs here. Make sure you have the necessary permissions on the token to run graphql queries and get job and run details.

6. Test the Connection

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

Test the connection and save the Service

7. 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 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.
Mark Deleted Pipelines (toggle): Set the Mark Deleted Pipelines toggle to flag pipelines as soft-deleted if they are not present anymore in the source system.

8. Schedule the Ingestion and Deploy

Scheduling can be set up at an hourly, daily, weekly, or manual 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.

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

Schedule the Ingestion Pipeline and Deploy

9. 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

Displaying Lineage Information

Steps to retrieve and display the lineage information for a DBT Cloud service. Note that only the metadata from the last run will be used for lineage.

Ingest Source and Sink Database Metadata: Identify both the source and sink database used by the DBT Cloud service for example Redshift. Ingest metadata for these database.
Ingest DBT Cloud Service Metadata: Finally, Ingest your DBT Cloud service.

By successfully completing these steps, the lineage information for the service will be displayed.

Troubleshooting

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

Missing Lineage

If lineage information is not displayed for a DBT Cloud service, follow these steps to diagnose the issue.

DBT Cloud Account: Make sure that the DBT cloud instance you are ingesting have the necessary permissions to fetch jobs and run graphql queries over the API.
Metadata Ingestion: Ensure that metadata for both the source and sink database is ingested and passed to the lineage system. This typically involves configuring the relevant connectors to capture and transmit this information.
Last Run Successful: Ensure that the Last Run for a Job is successful as OpenMetadata gets the metadata required to build the lineage using the last Run under a Job.