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This section provides guides and references to use the dbt Cloud connector. Configure and schedule dbt Cloud metadata workflows from the Collate UI:

Requirements

dbt Cloud Versions

Collate 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 dbt Cloud and fetch metadata.

dbt Cloud Permissions

The dbt Cloud 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

Metadata Ingestion

To ingest metadata from DBT Cloud, you need to create a service connection. The service connects DBT Cloud with Collate. Once you create a service, Collate automatically starts ingesting metadata.

Step 1: Add New Service

  1. In the left navigation, click Connections.
  2. On the Connections page, click Add New Service.
Add New Service

Step 2: Select a Service and Connector

From the service type dropdown, select Pipeline Services, then click the DBT Cloud connector tile. Select Service

Step 3: Add Service Name and Description

  • Enter a unique, descriptive Service Name. Collate identifies services by their service name. Enter a name that distinguishes this deployment from other DBT Cloud services you are ingesting metadata from.
  • Optional: Enter a Description for the service.
Add New Service Name
Note: The service name cannot be changed after it is set.

Step 4: Configure Connection Options

Specify where ingestion runs, provide your source credentials, and verify the connection.

Select Ingestion Runner

Select an Ingestion Runner: the runner where the ingestion pipeline will execute. Add Name and Select Ingestion Runner

Enter Connection Details

Enter the connection details for DBT Cloud. The right-hand panel in the UI displays inline help for each field. Configure Service Connection
  • Host: dbt Cloud Access URL eg.https://abc12.us1.dbt.com. Go to your dbt Cloud account settings to know your Access URL.
  • Discovery API URL: dbt Cloud Access URL eg. https://metadata.cloud.getdbt.com/graphql. Go to your dbt Cloud account settings to know your Discovery API url. Make sure you have /graphql at the end of your URL.
  • Account Id: The Account ID of your dbt Cloud Project. Go to your dbt Cloud account settings to know your Account Id. This will be a numeric value but in Collate this is parsed as a string.
  • Job Ids: Optional. Job IDs of your dbt Cloud Jobs 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 Collate this is parsed as a string. If not passed all Jobs under the Account id will be ingested.
  • Project Ids: Optional. Project IDs of your dbt Cloud Account to fetch metadata for. Look for the segment after “projects” in the URL. For instance, in a URL like https://cloud.getdbt.com/accounts/123/projects/87477/jobs/73659994, the job ID is 87477. This will be a numeric value but in Collate this is parsed as a string. If not passed all Projects under the Account id will be ingested. Note that if both Job Ids and Project Ids are passed then it will filter out the jobs from the passed projects. Any Job Ids not belonging to the Project Ids will also be filtered out.
  • 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.

Test Connection

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

Step 5: Configure Ingestion Options

In the What to Ingest step, use filter patterns to control which assets Collate ingests from your pipeline service. Filter patterns use regular expressions applied to pipeline names.

How Filter Patterns Work

  • Include: Add one or more comma-separated regular expressions. Collate ingests only assets whose names match at least one expression. Leave blank to include all assets.
  • Exclude: Add one or more comma-separated regular expressions. Collate skips any asset whose name matches an expression. Leave blank to exclude nothing.
Rules match asset names using one of five expressions:
  • contains: matches any name containing the value. For example, sales matches my_sales_data and sales_2024.
  • starts with: matches names beginning with the value. For example, prod_ matches prod_db and prod_schema.
  • ends with: matches names ending with the value. For example, _raw matches events_raw and logs_raw.
  • is exactly: matches the exact name only. For example, analytics matches only analytics.
  • matches regex: matches names using a regular expression. For example, ^prod_.*_v\d+$ matches prod_events_v1.
When both Include and Exclude are set, Exclude takes priority.
Tip: Leave the filter pattern empty to ingest all pipelines available in the source.
Filter Options The Pipeline section includes the following filter options:
  • Pipeline: Controls which pipelines (DAGs, jobs, or workflows) Collate ingests from the source.
Each section provides the following controls:
  • Scan Mode: You can choose between the following scan modes:
    • Scan all: Ingests every asset of that type the connector can access. This is the default.
    • Only specific: Enables include rules so only assets matching at least one rule are ingested.
  • Exclude system toggle: Use this toggle to automatically filter out system-reserved names defined by the connector — for example, Exclude system databases for the Databases section.
  • Always exclude: Add permanent exclusion rules (shown in red). Assets matching these rules are never ingested, regardless of include rules.
  • Preview: Shows a real-time summary of what will be in scope based on your current rules.
  • Include rules (available only in Only specific mode): Click + Add to define a rule. Added rules appear as chips; an asset is included if it matches any rule.
Tip: If AutoPilot is enabled, lineage between pipeline tasks and data assets is tracked automatically after the first metadata ingestion completes.

Step 6: Create & Deploy

Click Create & Deploy to deploy the agent and start the first metadata ingestion run. Collate saves the service configuration and immediately begins pulling metadata from the source. To monitor ingestion progress or view the service you just added, go to Connections in the left navigation and select your service.

Configure Metadata Agent and Schedule Ingestion

The Metadata Agent extracts pipelines, tasks, and other structural metadata from your source and keeps your Collate catalog in sync. It powers discovery, lineage, and governance across your data assets. When you click Create & Deploy, Collate automatically deploys a Metadata Agent for this service and triggers the first ingestion run. View its status and run history from the Agents tab on the service detail page. To configure the additional Metadata Agent and schedule ingestion, follow these steps:
  1. In the left navigation, click Connections and select your service.
  2. Click the Agents tab.
  3. Click Add Agent and select Metadata from the dropdown. Add Metadata Agent For some services, the dropdown is not available and clicking Add Agent takes you directly to the agent configuration page.
  4. On the Configure Ingestion page, do the following and click Next.
    • Name this Ingestion: Enter a unique recognizable name for this ingestion pipeline. Name this Ingestion
    • Agent Setup: Configure the core parameters for this agent. The following fields are available: Agent Setup
    • Filter Patterns: Apply include or exclude rules to scope which pipelines this agent ingests. These follow the same filter options described in Step 5. Filter Patterns
    • Scope & Behaviour: Control what metadata to include and how to handle deletions. Toggle each option on or off based on your needs: Scope & Behaviour
  5. On the Schedule Interval page, set when the agent runs:
    • Schedule: Choose a preset interval (Hourly, Daily, Weekly, Monthly) or enter a custom cron expression.
    • On-Demand: No automatic schedule; trigger the agent manually when needed.
    Schedule Interval
  6. Click Add to deploy the agent.

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.
  1. 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.
  2. 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.
dbt Cloud Lineage

Missing Lineage

If lineage information is not displayed for a dbt Cloud service, follow these steps to diagnose the issue.
  1. dbt Cloud Account: Make sure that the dbt Cloud instance you are ingesting has the necessary permissions to fetch jobs and run graphql queries over the API.
  2. 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.
  3. Last Run Successful: Ensure that the Last Run for a Job is successful as Collate gets the metadata required to build the lineage using the last Run under a Job.

Troubleshooting

dbt Cloud Troubleshooting

Learn more about how to troubleshoot common dbt Cloud connector issues and resolve configuration or ingestion errors.