dbt-jobs-as-code is a tool built to handle dbt Cloud Jobs as a well-defined YAML file. Being standard YAML, it is possible to use YAML anchors to reduce duplicate configuration across jobs.

A given dbt Cloud project can use both jobs-as-code and jobs-as-ui at the same time, without any conflict.

The way we differentiate jobs defined from code from the ones defined from the UI is that the code ones have a name ending with [[<identifier>]].

⚠️ Important: If you plan to use this tool but have existing jobs ending with [[...]] you should rename them before running any command.

Here is a short demonstration on how to set CI/CD with jobs as code

Terrraform is widely used to manage infrastructure as code. And a Terraform provider exists for dbt Cloud, able to manage dbt Cloud jobs (as well as projects, environments etc...).

Using Terraform requires some knowledge about the tool and requires managing/storing/sharing a state file, containing information about the state of the application.

With this package's approach, people don't need to learn another tool and can configure dbt Cloud using YAML, a language used across the dbt ecosystem:

• no state file required: the link between the YAML jobs and the dbt Cloud jobs is stored in the jobs name, in the [[<identifier>]] part
• YAML: dbt users are familiar with YAML and we created a JSON schema allowing people to verify that their YAML files are correct

This package uses poetry for dependency management. In the near future the package might be added to PyPi but for now the installation is manual, as follows:

1. clone this repository
2. run poetry install
3. run poetry run dbt-jobs-as-code to see the different list of commands available

The following environment variables are used to run the code:

• DBT_API_KEY: [Mandatory] The dbt Cloud API key to interact with dbt Cloud. Can be a Service Token (preferred, would require the "job admin" scope) or the API token of a given user
• DBT_BASE_URL: [Optional] By default, the tool queries https://cloud.getdbt.com, if your dbt Cloud instance is hosted on another domain, define it in this env variable (e.g. https://emea.dbt.com)

The CLI comes with a few different commands

• poetry run python src/main.py validate <config_file.yml>: validates that the YAML file has the correct structure
  • it is possible to run the validation offline, without doing any API call
  • or online using --online, in order to check that the different IDs provided are correct
• poetry run python src/main.py plan <config_file.yml>: returns the list of actions create/update/delete that are required to have dbt Cloud reflecting the configuration file
  • this command doesn't modify the dbt Cloud jobs
• poetry run python src/main.py sync <config_file.yml>: create/update/delete jobs and env vars overwrites in jobs to align dbt Cloud with the configuration file
  • ⚠️ this command will modify your dbt Cloud jobs if the current configuration is different from the YAML file
• poetry run python src/main.py import-jobs --config <config_file.yml> or poetry run python src/main.py import-jobs --account-id <account-id>: Queries dbt Cloud and provide the YAML definition for those jobs. It includes the env var overwrite at the job level if some have been defined
  • it is possible to restrict the list of dbt Cloud Job IDs by adding ... -j 101 -j 123 -j 234
  • once the YAML has been retrieved, it is possible to copy/paste it in a local YAML file to create/update the local jobs definition.
  • to move some ui-jobs to jobs-as-code, perform the following steps:
    • run the command to import the jobs
    • copy paste the job/jobs into a YAML file
    • change the import_ id of the job in the YML file to another unique identifier
    • rename the job in the UI to end with [[new_job_identifier]]
    • run a plan command to verify that no changes are required for the given job

The file src/schemas/load_job_schema.json is a JSON Schema file that can be used to verify that the YAML config files syntax is correct.

To use it in VSCode, install the extension YAML and add the following line at the top of your YAML config file (change the path if need be):

# yaml-language-server: $schema=../src/schemas/load_job_schema.json

An example of GitHub Action is provided in the example_cicd folder. This example requires having set the GitHub secret DBT_API_KEY.

You can copy/paste thie file in your own repo under .github/workflows. The current script except your jobs yml file to be saved under jobs/jobs.yml

After a PR on main is approved, the action will run a sync to compare the local yml file with the dbt Cloud configuration and will create/update/delete dbt Cloud jobs to align the two.

• Want to report a bug or request a feature? Let us know by opening an issue
• Want to help us build dbt? Check out the Contributing Guide