Create an Azure Managed Lustre file system using Terraform

In this article, you use Terraform to create an Azure Managed Lustre file system.

Terraform enables the definition, preview, and deployment of cloud infrastructure. Using Terraform, you create configuration files using HCL syntax. The HCL syntax allows you to specify the cloud provider - such as Azure - and the elements that make up your cloud infrastructure. After you create your configuration files, you create an execution plan that allows you to preview your infrastructure changes before they're deployed. Once you verify the changes, you apply the execution plan to deploy the infrastructure.

In this article, you learn how to:

Prerequisites

• Install and configure Terraform

Implement the Terraform code

1. Create a directory in which to test the sample Terraform code and make it the current directory.

2. Create a file named providers.tf and insert the following code:

   terraform {
     required_version = ">=1.0"
   
     required_providers {
       azurerm = {
         source  = "hashicorp/azurerm"
         version = "~>3.0"
       }
       random = {
         source  = "hashicorp/random"
         version = "~>3.0"
       }
     }
   }
   
   provider "azurerm" {
     features {}
   }
   

3. Create a file named main.tf and insert the following code:

   resource "random_pet" "rg_name" {
     prefix = var.resource_group_name_prefix
   }
   
   resource "azurerm_resource_group" "rg" {
     location = var.resource_group_location
     name     = random_pet.rg_name.id
   }
   
   resource "random_string" "azurerm_virtual_network_name" {
     length  = 13
     lower   = true
     numeric = false
     special = false
     upper   = false
   }
   
   resource "azurerm_virtual_network" "example" { 
     name = coalesce(var.virtual_network_name, "vnet-${random_string.azurerm_virtual_network_name.result}")
     resource_group_name = azurerm_resource_group.rg.name
     address_space = ["10.0.0.0/16"] 
     location = azurerm_resource_group.rg.location 
   }
   
   resource "random_string" "azurerm_subnet_name" {
     length  = 13
     lower   = true
     numeric = false
     special = false
     upper   = false
   }
   
   resource "azurerm_subnet" "example" { 
     name = coalesce(var.subnet_name, "subnet-${random_string.azurerm_subnet_name.result}")
     resource_group_name = azurerm_resource_group.rg.name 
     virtual_network_name = azurerm_virtual_network.example.name 
     address_prefixes = ["10.0.2.0/24"]
   }
   
   resource "random_string" "azurerm_amlfs_name" {
     length  = 13
     lower   = true
     numeric = false
     special = false
     upper   = false
   }
   
   resource "azurerm_managed_lustre_file_system" "example" { 
     name = coalesce(var.amlfs_name, "amlfs-${random_string.azurerm_amlfs_name.result}")
     resource_group_name = azurerm_resource_group.rg.name
     location = azurerm_resource_group.rg.location 
     sku_name = var.amlfs_sku_name
     subnet_id = azurerm_subnet.example.id 
     storage_capacity_in_tb = var.amlfs_storage_capacity_in_tb 
     zones = ["1"] 
     maintenance_window {
       day_of_week = var.amlfs_maintenance_day_of_week
       time_of_day_in_utc = var.amlfs_maintenance_time_of_day
     }
   }
   

4. Create a file named variables.tf and insert the following code:

   variable "resource_group_name_prefix" {
     type        = string
     default     = "rg"
     description = "Prefix of the resource group name that's combined with a random ID so name is unique in your Azure subscription."
   }
   
   variable "resource_group_location" {
     type        = string
     default     = "eastus"
     description = "Location of the resource group."
   }
   
   variable "virtual_network_name" {
     type        = string
     description = "The name of the virtual network resource. The value will be randomly generated if blank."
     default     = ""
   }
   
   variable "subnet_name" {
     type        = string
     description = "The name of the virtual network subnet. The value will be randomly generated if blank."
     default     = ""
   }
   
   variable "amlfs_name" {
     type        = string
     description = "The name of the Manage Lustre file system resource. The value will be randomly generated if blank."
     default     = ""
   }
   
   variable "amlfs_sku_name" {
     type        = string
     default     = "AMLFS-Durable-Premium-40"
     validation {
       condition     = contains(["AMLFS-Durable-Premium-40", "AMLFS-Durable-Premium-125", "AMLFS-Durable-Premium-250", "AMLFS-Durable-Premium-500"], var.amlfs_sku_name)
       error_message = "The SKU value must be one of the following: AMLFS-Durable-Premium-40, AMLFS-Durable-Premium-125, AMLFS-Durable-Premium-250, AMLFS-Durable-Premium-500."
     }
     description = "SKU name for the Azure Managed Lustre file system."
   }
   
   variable "amlfs_storage_capacity_in_tb" {
     type        = number
     default     = 48
     description = "The size of the Managed Lustre file system, in TiB. This might be rounded up."
   }
   
   variable "amlfs_maintenance_day_of_week" {
     type        = string
     default     = "Saturday"
     validation {
       condition     = contains(["Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday"], var.amlfs_maintenance_day_of_week)
       error_message = "The maintenance day of week value must be one of the following: Sunday, Monday, Tuesday, Wednesday, Thursday, Friday, Saturday."
     }
     description = "Day of the week on which the maintenance window will occur."
   }
   
   variable "amlfs_maintenance_time_of_day" {
     type        = string
     default     = "02:00"
     description = "The time of day (in UTC) to start the maintenance window."
   }
   

5. Create a file named outputs.tf and insert the following code:

   output "resource_group_name" {
     value = azurerm_resource_group.rg.name
   }
   
   output "virtual_network_name" {
     value = azurerm_virtual_network.example.name
   }
   
   output "subnet_name" {
     value = azurerm_subnet.example.name
   }
   
   output "managed_lustre_file_system_name" {
     value = azurerm_managed_lustre_file_system.example.name
   }
   
   output "amlfs_sku_name" {
     value = azurerm_managed_lustre_file_system.example.sku_name
   }
   
   output "amlfs_storage_capacity_in_tb" {
     value = azurerm_managed_lustre_file_system.example.storage_capacity_in_tb
   }
   

Initialize Terraform

Run terraform init to initialize the Terraform deployment. This command downloads the Azure provider required to manage your Azure resources.

terraform init -upgrade

Key points:

• The -upgrade parameter upgrades the necessary provider plugins to the newest version that complies with the configuration's version constraints.

Create a Terraform execution plan

Run terraform plan to create an execution plan.

terraform plan -out main.tfplan

Key points:

• The terraform plan command creates an execution plan, but doesn't execute it. Instead, it determines what actions are necessary to create the configuration specified in your configuration files. This pattern allows you to verify whether the execution plan matches your expectations before making any changes to actual resources.
• The optional -out parameter allows you to specify an output file for the plan. Using the -out parameter ensures that the plan you reviewed is exactly what is applied.

Apply a Terraform execution plan

Run terraform apply to apply the execution plan to your cloud infrastructure.

terraform apply main.tfplan

Key points:

• The example terraform apply command assumes you previously ran terraform plan -out main.tfplan.
• If you specified a different filename for the -out parameter, use that same filename in the call to terraform apply.
• If you didn't use the -out parameter, call terraform apply without any parameters.

Verify the results

Clean up resources

When you no longer need the resources created via Terraform, do the following steps:

1. Run terraform plan and specify the destroy flag.

   terraform plan -destroy -out main.destroy.tfplan
   

   Key points:

   • The terraform plan command creates an execution plan, but doesn't execute it. Instead, it determines what actions are necessary to create the configuration specified in your configuration files. This pattern allows you to verify whether the execution plan matches your expectations before making any changes to actual resources.
   • The optional -out parameter allows you to specify an output file for the plan. Using the -out parameter ensures that the plan you reviewed is exactly what is applied.

2. Run terraform apply to apply the execution plan.

   terraform apply main.destroy.tfplan
   

Troubleshoot Terraform on Azure

Troubleshoot common problems when using Terraform on Azure

Next steps

Next, you can explore more about Azure Managed Lustre.