How to Create/Edit an Environment

Navigate to the Environments page

To create a new environment click the New Environment button.

Environment Settings are separated into different tabs.

Basic information

This tab has the base information for the environment.

• The name to be displayed on the launchpad
• The Project the environment should be associated with
• The type of environment (development, test or prod). It is best practice for users to perform their work in a development environment and production jobs to run in a production environment which is typically more governed.

Stack Services

Define which tools will be enabled for this environment. At least one service must be enabled.

Available services include:

• LOAD (Airbyte)
• TRANSFORM (dbt and VS Code)
• OBSERVE (dbt docs)
• ORCHESTRATE (Airflow)
• ANALYZE (Superset)

Services Configuration

The services enabled for the environment may require additional configurations. This tab is where the services will be configured.

• TRANSFORM (dbt & VS Code) requires:
  • dbt project path: The path the location of the dbt_project.yml this allows you to either have the dbt project at the root of your git repository or in some sub-folder. If you have implemented the recommended folder structure this will be transform. If your dnt project is at the root, leave it blank.
  • dbt profile name: dbt profile name as defined in dbt_project.yml with the key profile. The standard is default.

• ORCHESTRATE (Airflow) requires:
  • branch: Determines git branch to synchronize to Airflow. This allows you to have one branch for a development environment and main for a production environment. In other words, in development we recommend making this field airflow_development and main in production. Please be aware that you will need to create an airflow_development branch in your repository.
  • dbt profiles path: The location where Airflow will find dbt profiles.yml file to use during a dbt run. This should be automate/dbt. Please be aware that you will need to create the automate anddbt folders as well as the profiles.yml in your repository.
  • YAML DAGs path: When using yml based Airflow DAGs Airflow will look for the yml files in this location. We recommend this be set to orchestrate/dags. Please be aware that you will need to create the orchestrate and dags folders in your repository.
  • Python DAGs path: This is the location Airflow will look for the DAG definition files. We recommend this be set to orchestrate/dag_yml_definitions. Please be aware that you will need to create the orchestrate and dag_yml_definitions folders in your repository.
• OBSERVE (Docs) requires:
  • branch: Here we specify the branch that will be synchronized for production dbt docs. This branch must exist in your git repository.