Dynamic Map(object) how to create?

Terraform
1

I’m in the process of learning Terraform, the questions I have are based on the code below. This is not all of the code… The code does function now.

module "route53-health-checks" {

  source = "./route53-health-checks"

  for_each      = var.map
  environment   = each.value["environment"]   #var.environment
  domain_name   = each.value["domain_name"]   #var.domain_name
  resource_path = each.value["resource_path"] #var.resource_path
}




variable "map" {
  type = map(object({
    environment   = string
    domain_name   = string
    resource_path = string
  }))
  default = {
    "1" = {
      environment   = "all"
      domain_name   = "mywebsite.com"
      resource_path = "/"
    }
    "2" = {
      environment   = "misc1"
      domain_name   = "myothersite.com"
      resource_path = "/onlineservices/account/login.aspx"
    }
    "3" = {
      environment   = "misc2"
      domain_name   = "stuffhere.com"
      resource_path = "/"
    }
  }
}

So i have a module that I call using the for_each = var.map

The variable “map” default section I had to create by hand… How can i automate that based of some sort of external input… file etc…? I will have possibly hundreds of entries… Manually creation is not going to cut it.

I have seen things like leveraging Dynamic Blocks, but looks like that is not recommended… Any help would be greatly appreciated…

thanks

2

I’d say that common patterns could be json, yaml or csv files utilising terraform functions jsondecode, yamldecode and csvdecode.

3

Thank you… the csvdecode is exactly what I was looking for. For anybody else here is a great link on how to leverage csvdecode…

Watch Jesse Loudon discuss DRY Coding with Terraform, CSVs, and ForEach is a HashiTalk about leveraging the power of Terraform’s csvdecode function to produce a list of maps representing data stored in Comma-separated Value (CSV) format. By combining csvdecode with Terraform’s for_each meta argument we can achieve a DRY / low-code methodology to deploy resources at scale from large datasets.