Project Configuration

Introduction

Project Configuration is a core concept in Atlas that allows you to manage your database schema in a more advanced way. When using the Atlas Terraform Provider, you can inject a project configuration to customize its behavior.

How it works

The atlas_schema resource in the Terraform provider accepts a config attribute where you can provide the content of an Atlas project file. Full documentation is available here.

Guide: Using Variables for Multiple Environments

In this guide, we will demonstrate how to use a custom configuration to manage different database connection details for multiple environments (e.g., staging vs. production) using a single Terraform configuration.

Step 1: Set up the project

First, set up your Terraform project. Create a main.tf file with the provider configuration:

main.tf

terraform {
  required_providers {
    atlas = {
      source  = "ariga/atlas"
      version = "~> 0.9.7"
    }
  }
}

provider "atlas" {
  dev_url = "docker://postgres/15"
}

Initialize the project by running:

terraform init

Step 2: Provision local databases

Next, we will spin up two PostgreSQL databases to simulate a staging and production environment. This requires Docker.

docker run --name postgres-staging -p 5432:5432 -e POSTGRES_PASSWORD=pass -d postgres:15
docker run --name postgres-prod -p 5433:5432 -e POSTGRES_PASSWORD=pass -d postgres:15

Step 3: Define the AtlasSchema resource

Now, update your main.tf to define the atlas_schema resource with a custom configuration that uses variables.

main.tf

terraform {
  required_providers {
    atlas = {
      source  = "ariga/atlas"
      version = "~> 0.9.7"
    }
  }
}

provider "atlas" {
  dev_url = "docker://postgres/15"
}

locals {
  # Define connection details for each environment
  environments = {
    staging = {
      url = "postgres://postgres:pass@localhost:5432/postgres?sslmode=disable"
    }
    production = {
      url = "postgres://postgres:pass@localhost:5433/postgres?sslmode=disable"
    }
  }
  # Atlas project configuration
  atlas_config = <<-EOT
    variable "url" {
      type = string
    }
    env "tf" {
      url = var.url
    }
  EOT
}

resource "atlas_schema" "multi_env" {
  env_name  = "tf"
  config    = local.atlas_config
  variables = jsonencode({
    url = local.environments[terraform.workspace].url
  })
  hcl = <<-EOT
    schema "public" {}
    table "users" {
      schema = schema.public
      column "id" {
        type = int
        null = false
      }
      primary_key {
        columns = [column.id]
      }
    }
  EOT
}

In this configuration:

• We use terraform.workspace to dynamically select the environment.
• The atlas_config local variable holds the content of our atlas.hcl file. It declares a url variable.
• The atlas_schema resource uses jsonencode to pass the correct URL to the Atlas configuration based on the active workspace.

Step 4: Create and apply to staging

Let's create and switch to the staging workspace.

terraform workspace new staging
terraform apply -auto-approve

The output should look like this:

Terraform used the selected providers to generate the following execution plan. Resource actions are
indicated with the following symbols:
  + create

Terraform will perform the following actions:

  # atlas_schema.multi_env will be created
  + resource "atlas_schema" "multi_env" {
      + config    = <<-EOT
            variable "url" {
              type = string
            }
            env "tf" {
              url = var.url
            }
        EOT
        ...
      }
    }
    ...

Plan: 1 to add, 0 to change, 0 to destroy.
atlas_schema.multi_env: Creating...
atlas_schema.multi_env: Creation complete after 2s [id=7ab6d901-9df0-a60a-9d86-9e66a57ef105]
╷
│ Warning: Atlas Plan
│ 
│   with atlas_schema.multi_env,
│   on main.tf line 38, in resource "atlas_schema" "multi_env":
│   38: resource "atlas_schema" "multi_env" {
│ 
│ The following SQL statements will be executed:
│ 
│ 
│ CREATE TABLE "public"."users" (
│   "id" integer NOT NULL,
│   PRIMARY KEY ("id")
│ );

Apply complete! Resources: 1 added, 0 changed, 0 destroyed.

Verify that the users table was created in the staging database:

docker exec -it postgres-staging psql -U postgres -d postgres -c "\\dt"

The output should look like this:

         List of relations
 Schema | Name  | Type  |  Owner   
--------+-------+-------+----------
 public | users | table | postgres
(1 row)

Step 5: Apply to production

Now, let's deploy the same schema to the production environment.

terraform workspace new production
terraform workspace select production
terraform apply -auto-approve

Verify that the users table was created in the production database:

docker exec -it postgres-prod psql -U postgres -d postgres -c "\\dt"

You have now managed two different environments using a single, parameterized Terraform configuration.