Configuring sources.yml for Dev and Prod Environments in dbt using Target Variables

📘Introduction

In this hands-on dbt tutorial, you’ll learn how to configure your sources.yml file to handle multiple environments (DEV and PROD) dynamically using dbt’s powerful target variable. This will ensure that your models always connect to the correct database, based on the environment you are currently working in, without needing any manual changes.

↔️ DEV and PROD environments in dbt

Before we dive in, have a look at our previous post:

Configuring DEV an PROD Environments in dbt

📘Introduction In this hands-on dbt tutorial, you’ll learn how to configure separate development (DEV) and production (PROD) environments to safely build, test, and deploy your data models. We’ll walk through why environment separation matters and how to configure your profiles.yml so you can switch between environments with

Deep Learning Nerds | The ultimate Learning Platform for AI and Data ScienceData Engineer

In that tutorial, you learned how to configure separate DEV and PROD environments in dbt.

Now, we’ll take it a step further by showing how to use dbt’s built-in target variable to make your sources.yml dynamically switch between DEV and PROD without changing any code.

⚙️ Target variable in our example project

Here’s the profiles.yml for our example project dlnerds_university: