In this section, we provide guides and references to use the dbt Cloud connector.
Configure and schedule dbt Cloud metadata and profiler workflows from the OpenMetadata UI:
How to Run the Connector Externally
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, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.
Requirements
Python Requirements
We have support for Python versions 3.8-3.11
Metadata Ingestion
All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to DBT cloud.
In order to create and run a Metadata Ingestion workflow, we will follow the steps to create a YAML configuration able to connect to the source, process the Entities if needed, and reach the OpenMetadata server.
The workflow is modeled around the following JSON Schema
1. Define the YAML Config
This is a sample config for dbt Cloud:
Source Configuration - Service Connection
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.
discoveryAPI: 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.
accountId: 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.
jobId: 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.
Source Configuration - Source Config
The sourceConfig is defined here:
dbServiceNames: Database Service Name for the creation of lineage, if the source supports it.
includeTags: Set the 'Include Tags' toggle to control whether to include tags as part of metadata ingestion.
includeUnDeployedPipelines: Set the 'Include UnDeployed Pipelines' toggle to control whether to include un-deployed pipelines as part of metadata ingestion. By default it is set to true
markDeletedPipelines: Set the Mark Deleted Pipelines toggle to flag pipelines as soft-deleted if they are not present anymore in the source system.
pipelineFilterPattern and chartFilterPattern: Note that the pipelineFilterPattern and chartFilterPattern both support regex as include or exclude.
Sink Configuration
To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest.
Workflow Configuration
The main property here is the openMetadataServerConfig, where you can define the host and security provider of your OpenMetadata installation.
Logger Level
You can specify the loggerLevel depending on your needs. If you are trying to troubleshoot an ingestion, running with DEBUG will give you far more traces for identifying issues.
JWT Token
JWT tokens will allow your clients to authenticate against the OpenMetadata server. To enable JWT Tokens, you will get more details here.
You can refer to the JWT Troubleshooting section link for any issues in your JWT configuration.
Store Service Connection
If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.
If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.
Store Service Connection
If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.
If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.
SSL Configuration
If you have added SSL to the OpenMetadata server, then you will need to handle the certificates when running the ingestion too. You can either set verifySSL to ignore, or have it as validate, which will require you to set the sslConfig.caCertificate with a local path where your ingestion runs that points to the server certificate file.
Find more information on how to troubleshoot SSL issues here.
2. Run with the CLI
First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration, you will be able to extract metadata from different sources.