Terraform Security:

Last Updated on February 14, 2024 by Arnav Sharma

Let’s assume you want to configure resources where attributes require similar structures. A list-to-map conversion with objects makes this more manageable.


Consider this scenario: you have a list of property names. You want to create a map where each property name is a key, and the value is an object defining that property’s type.


Define Your List:

variable "property_list" {
  type = list(string)
  default = ["name", "description", "type"]

Create an Empty Map:

locals {
    property_map = {}

Use a for loop:

locals {
  property_map = {
    for prop in var.property_list : prop => {
      "type" = "string"  # Assign a default type


  • We start with a variable property_list containing the names of your properties.
  • An empty map, property_map, is created within a locals block.
  • The for loop iterates over each prop (property name) in the property_list.
  • Inside the loop, it constructs an object with the current prop as the key. The object has a single attribute, “type”, set to “string” (you can customize this).
  • This object is then added to the property_map.


The resulting property_map would look like this:

  "name"        = { "type" = "string" }
  "description" = { "type" = "string" }
  "type"        = { "type" = "string" }


You could then use this property_map to dynamically create resource configurations, feeding these objects into attributes.

Key Points

  • locals are used to define values that can be referenced elsewhere in your Terraform configuration.
  • for loops are essential for transforming data structures in Terraform.
  • Customize the object’s structure within the for loop to suit your specific use case (add more attributes, change types, etc.).

Example of Azure VM:

Let’s say you need to create several Azure VMs with similar configurations, but you want to vary the VM names and possibly some other attributes.

provider "azurerm" {
  # ... Your Azure provider configuration ...

# Variables for VM configuration
variable "vm_names" {
  type = list(string)
  default = ["webserver-01", "webserver-02", "dbserver"]

variable "base_vm_config" {
  type = map(object({
    size          = string
    resource_group_name = string
    location          = string
    image_urn         = string
    admin_username    = string
    admin_password    = string
  default = {
    size          = "Standard_B2s"
    resource_group_name = "my-resource-group" 
    location          = "eastus" 
    image_urn         = "Canonical:UbuntuServer:18.04-LTS:latest"
    admin_username    = "adminuser"
    admin_password    = "your_secure_password" 

# Customize individual VM configurations
locals {
  vm_configs = {
    for vm_index, vm_name in var.vm_names : vm_name => merge(var.base_vm_config, {
      name = vm_name,
      size = (vm_index == 2 ? "Standard_D2s_v3" : var.base_vm_config.size), 
      tags = {
        "role" = (vm_name == "dbserver" ? "database" : "web")

# Iterate and create VMs using the map
resource "azurerm_virtual_machine" "vm" {
  for_each = local.vm_configs

  # Access VM settings with each.key (VM name) and each.value 
  name                = each.key 
  size                = each.value.size
  resource_group_name = each.value.resource_group_name
  location            = each.value.location

  # ... (other VM configurations using each.value: network_interface_ids, storage_image_reference, etc.)

  os_profile {
    computer_name  = each.key
    admin_username = var.base_vm_config.admin_username
    admin_password = var.base_vm_config.admin_password

  os_profile_linux_config {
    disable_password_authentication = false


  1. provider “azurerm”: Configures the Azure Resource Manager provider. You’ll need to have this set up with your Azure credentials.
  2. variable “vm_names”: Defines a list of your desired Azure VM names.
  3. variable “base_vm_config”: A map storing the core configuration that will be shared across most of your VMs.
  4. locals “vm_configs”:
    • for loop: Iterates over both the name and index (vm_index) of each VM.
    • merge: Combines the base_vm_config with customizations:
      • name: Sets the VM name.
      • size: Conditionally assigns a different size for the third VM.
      • tags: Assigns role-based tags for identification.
  5. resource “azurerm_virtual_machine” “vm”:
    • for_each: Iterates over the vm_configs map.
    • each.key: Provides the VM name (e.g., “webserver-01”).
    • each.value: Provides the entire configuration object for that specific VM.
    • Example usage: Access each.value.sizeeach.value.tags, etc.

FAQ: Convert List to Map

Q: How can you use Terraform to convert a list into a map?

In Terraform, the tomap function is used to convert a list into a map. This is particularly useful when you want to manipulate structured data within Terraform’s HCL (HashiCorp Configuration Language). The tomap function requires all the elements in the list to be of the same general type, ensuring that the resulting map is consistent. This function is beneficial in various cloud infrastructure scenarios, where you need to create specific structures out of list of strings, for example, transforming resource attributes into a more usable format. The key in the resulting map is the property name, and the value can be another map or object, depending on the input data used in Terraform. For detailed examples and further understanding, you can refer to HashiCorp’s documentation or community resources like HashiCorp Discuss.

Q: What are the challenges in converting a list to a map using Terraform and how can they be addressed?

When using Terraform to convert a list to a map, a primary challenge is ensuring that the input list conforms to a specific structure that Terraform can interpret. The list elements must be of a consistent type, and if the intended value is another map or object, this structure must be clearly defined. Another challenge is setting the key-value pairs appropriately; the key is typically an identifier like an index or a unique property name, while the value is the data you want to represent. To address these challenges, it’s important to plan the structure of the input list carefully and understand how the tomap function manipulates data. Additionally, referring to resources like HashiCorp Discuss, Microsoft Azure’s documentation, or blogs with years of experience in programming and infrastructure support can provide practical insights and examples.

Q: What is the significance of the tomap function in Terraform’s HCL?

The tomap function in Terraform’s HCL (HashiCorp Configuration Language) holds significant importance as it allows users to convert a list into a map, thereby expanding the ways in which data can be structured and manipulated. In HCL, a map variable is a collection where each value is accessed by a key, making it essential for representing complex data structures efficiently. The tomap function simplifies the process of creating these structures, especially when the input data is in list format. It’s particularly useful in cloud infrastructure management, where structured data and resource attributes often need to be represented in a map format for clearer organization and easier access. This function, along with Terraform’s other data manipulation capabilities, demonstrates the flexibility and power of HCL in infrastructure as code, allowing for more efficient and readable code.

Q: How does Terraform’s tomap function facilitate cloud infrastructure management?

Terraform’s tomap function plays a crucial role in cloud infrastructure management by enabling the conversion of a list into a map, which is essential for handling structured data in a more organized manner. In the context of HashiCorp’s Terraform, particularly in cloud environments like Azure, the tomap function allows users to represent resource attributes and input variables in a map format. This is especially useful when dealing with complex configurations where you need to nest data structures or manipulate boolean values. The tomap function requires all elements of the input list to be of a consistent and specific structure, thus ensuring that the resulting map is reliable and usable in various programming and infrastructure contexts. By using this function, Terraform users can expand their capability to efficiently manage and support complex cloud infrastructures.

Q: What are the programming considerations when using Terraform’s tomap function to convert a list to a map?

When using Terraform’s tomap function to convert a list to a map, several programming considerations must be taken into account. Firstly, the structure of the input list is paramount; it should represent data in a format that Terraform can interpret, usually as a list of strings where each string is a key-value pair. The tomap function is used to generate a map variable where the key is typically an index or a unique identifier, and the value is the actual data. This process often involves using functions like element and index to manipulate the input data. Another consideration is the consistency in data types, as Terraform’s HCL (HashiCorp Configuration Language) requires all elements in a list to be of the same type to convert them into a map. This function is a powerful tool to represent infrastructure as code, allowing programmers to manipulate and structure data in a format that is more suitable for cloud resources and configurations.

Q: Can the tomap function in Terraform handle complex data structures like nested maps or objects?

Yes, the tomap function in Terraform can handle complex data structures, including nested maps or objects. This capability is particularly useful in scenarios where you need to create a map variable that not only represents simple key-value pairs but also more intricate structures where the value is another map or object. For instance, in cloud infrastructure management, especially with providers like Azure, it’s common to represent nested resource attributes or configurations. Using Terraform’s tomap function in such instances allows for a more structured and readable format, essential for maintaining clarity in infrastructure code. However, it’s important to ensure that the input list or structure being converted into a map has a consistent format and type, as HCL requires this for proper interpretation and manipulation of data.

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