Data sources in Terraform are used to get information about resources external to Terraform, and use them to set up your Terraform resources. For example, a list of IP addresses a cloud provider exposes.
We can find excellent examples of data source usage in the AWS provider docs:
variable "vpc_id" {}
data "aws_vpc" "selected" {
id = var.vpc_id
}
resource "aws_subnet" "example" {
vpc_id = data.aws_vpc.selected.id
availability_zone = "us-west-2a"
cidr_block = cidrsubnet(data.aws_vpc.selected.cidr_block, 4, 1)
}In this scenario, we may have created our aws_vpc manually, because it also contains other manually created resources, and now we want to start adding Terraform managed resources to it.
In order to do this, we use the aws_vpc data source to find the manually created aws_vpc, and then use its properties to configure our aws_subnet.
Another fancy use case would be to use the GitHub provider Pull Requests data source to list all Pull Requests, and then provision an on-demand preview environment for each Pull Request. It would go along the lines of:
data "github_repository_pull_requests" "pull_requests" {
base_repository = "example-repository"
base_ref = "main"
state = "open"
}
module “preview-environment” {
for_each = data.github_repository_pull_requests.pull_requests.results
name = each.value.title
commit_sha = each.value.head_sha
// ...
}By default, Terraform will refresh all data sources before creating a plan. You can also explicitly refresh all data sources by running terraform refresh.
Occasionally you’ll have data sources that change very often and would like to keep your resources in sync with those changes. The easiest way to achieve this is to just run Terraform every few minutes or so, do a refresh, and apply all resulting changes.
You could also use something akin to Spacelift’s Drift Detection to automate this process and make sure it doesn’t interfere with your manual Terraform executions.
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