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Provisioning schemas (named databases) with Terraform using Atlas

Terraform is an Infrastructure as Code (IaC) tool that allows teams to automate and manage their infrastructure through code. It streamlines the process of provisioning, updating, and maintaining infrastructure resources while reducing human error.

Many teams rely on managed SQL databases, such as Amazon RDS on AWS or Cloud SQL on GCP, and use the relevant Terraform provider (AWS, GCP) to provision these databases. For example:

resource "aws_db_instance" "default" {
allocated_storage = 10
db_name = "mydb"
engine = "mysql"
engine_version = "8.0"
instance_class = "db.t3.micro"
username = "foo"
password = "foobarbaz"
parameter_group_name = "default.mysql8.0"
skip_final_snapshot = true

When preparing the infrastructure for the deployment of applications, IaC need to ensure the required schemas (named databases) exist on the database instance in which tables and other database resources will be created.

This can be done manually by connecting to the database instance and running a command such as:

CREATE SCHEMA "products";

Such manual interactions with infrastructure is undesired in the context of IaC pipelines which aim to eliminate all manual provisioning steps and replace them with automation.

To achieve the same goal, Terraform users may use the Atlas Terraform Provider which allows teams to provision database resources as part of their IaC pipelines. Let's see how.

Start by adding the Atlas provider as a dependency of your Terraform project:

terraform {
required_providers {
atlas = {
source = "ariga/atlas"
version = "~> 0.4.5"

When storing schema definitions, many database engines perform some form of normalization. Meaning, despite us providing a specific definition of some aspect of the schema, the database will store it in another, equivalent form. Therefore, in certain situations it may appear to Atlas as if some diff exists between the desired and inspected schemas, whereas in reality there is none.

To overcome these situations, we use the atlas_schema data source to provide Atlas with a connection string to a Dev-Database. This database is used to normalize the schema prior to planning migrations and for simulating changes to ensure their applicability before execution.

Before running terraform apply for this project, make sure you have a locally running, empty database. You can use Docker to spin one up:

docker run --rm --name devdb -d -p 3306:3306 -e MYSQL_ROOT_PASSWORD=pass mysql:8

Next, normalize the schema definition containing three schemas: users, products and admin:

// Load (and normalize) the desired schema from an SQL file.
data "atlas_schema" "db" {
src = <<EOF
schema "users" {}
schema "products" {}
schema "admin" {}
dev_db_url = "mysql://root:pass@:3306/"

The src attribute defines the desired schema we wish to apply to our target database. Next let's see how we can apply this schema to our target database:

// Sync the state of the target database with the desired state.
resource "atlas_schema" "db" {
hcl = data.atlas_schema.db.hcl
url = "mysql://root:pass@localhost:3306/"
exclude = [ "users.*", "products.*", "admin.*" ]
dev_db_url = "mysql://root:pass@:3306/"

Let's unpack what's going on here:

  • hcl - sets the normalized schema from the data source as the desired state for the database.
  • url - is the connection string to the target database that we want to manage. To learn how to construct the connection string from an existing managed database see this guide.
  • exclude - tells Atlas to ignore any sub-resources inside the three schemas users, products, and admin. This way if tables are later created under these schemas they will not be dropped by Terraform in future terraform apply runs.

See it in action

Since we added a new provider to our project, let's first re-initialize the project:

terraform init

Finally, let's run apply:

terraform apply
data.atlas_schema.db: Reading...
data.atlas_schema.db: Read complete after 0s [id=e9CBNHJqQOfAb7WRlAt83w]

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:

# will be created
+ resource "atlas_schema" "market" {
+ exclude = [
+ "users.*",
+ "products.*",
+ "admin.*",
+ hcl = <<-EOT
schema "admin" {
charset = "utf8mb4"
collate = "utf8mb4_0900_ai_ci"
schema "products" {
charset = "utf8mb4"
collate = "utf8mb4_0900_ai_ci"
schema "users" {
charset = "utf8mb4"
collate = "utf8mb4_0900_ai_ci"
+ id = (known after apply)
+ url = (sensitive value)

Plan: 1 to add, 0 to change, 0 to destroy.
│ Warning: Atlas Plan

│ with,
│ on line 23, in resource "atlas_schema" "market":
23: resource "atlas_schema" "market" {

│ The following SQL statements will be executed:

│ -- add new schema named "admin"
│ -- add new schema named "products"
│ CREATE DATABASE `products`
│ -- add new schema named "users"

Do you want to perform these actions?
Terraform will perform the actions described above.
Only 'yes' will be accepted to approve.

We type yes to apply our plan:

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

Let's re-run apply, to make sure everything is in order:

terraform apply
data.atlas_schema.db: Reading...
data.atlas_schema.db: Read complete after 0s [id=e9CBNHJqQOfAb7WRlAt83w] Refreshing state... [id=mysql://localhost:3306/]

No changes. Your infrastructure matches the configuration.

Terraform has compared your real infrastructure against your configuration and found no differences, so no changes are needed.

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

Great! Everything is in sync.

Wrapping up

In this guide, we demonstrated how to use Terraform and the Atlas Terraform Provider to provision empty schemas (named databases) in existing DB instances as part of your Infrastructure-as-Code pipelines.

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