Quickstart: Deploy an Azure Linux Container Host for AKS cluster using Terraform

Get started with the Azure Linux Container Host using Terraform to deploy an Azure Linux Container Host cluster. After installing the prerequisites, you implement the Terraform code, initialize Terraform, and create and apply a Terraform execution plan.

Terraform enables the definition, preview, and deployment of cloud infrastructure. With Terraform, you create configuration files using HCL syntax. The HCL syntax allows you to specify the cloud provider and 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.


The example code in this article is located in the Microsoft Terraform GitHub repo.


Create an SSH key pair

To access AKS nodes, you connect using an SSH key pair (public and private), which you generate using the ssh-keygen command. By default, these files are created in the ~/.ssh directory. Running the ssh-keygen command overwrites any SSH key pair with the same name already existing in the given location.

  1. Go to https://shell.azure.com to open Cloud Shell in your browser.

  2. Run the ssh-keygen command. The following example creates an SSH key pair using RSA encryption and a bit length of 4096:

    ssh-keygen -t rsa -b 4096

For more information about creating SSH keys, see Create and manage SSH keys for authentication in Azure.

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:

        # Generate random resource group name
        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_id" "log_analytics_workspace_name_suffix" {
          byte_length = 8
        resource "azurerm_log_analytics_workspace" "test" {
          location            = var.log_analytics_workspace_location
          # The WorkSpace name has to be unique across the whole of azure;
          # not just the current subscription/tenant.
          name                = "${var.log_analytics_workspace_name}-${random_id.log_analytics_workspace_name_suffix.dec}"
          resource_group_name = azurerm_resource_group.rg.name
          sku                 = var.log_analytics_workspace_sku
        resource "azurerm_log_analytics_solution" "test" {
          location              = azurerm_log_analytics_workspace.test.location
          resource_group_name   = azurerm_resource_group.rg.name
          solution_name         = "ContainerInsights"
          workspace_name        = azurerm_log_analytics_workspace.test.name
          workspace_resource_id = azurerm_log_analytics_workspace.test.id
          plan {
            product   = "OMSGallery/ContainerInsights"
            publisher = "Microsoft"
        resource "azurerm_kubernetes_cluster" "k8s" {
          location            = azurerm_resource_group.rg.location
          name                = var.cluster_name
          resource_group_name = azurerm_resource_group.rg.name
          dns_prefix          = var.dns_prefix
          tags                = {
            Environment = "Development"
          default_node_pool {
            name       = "azurelinuxpool"
            vm_size    = "Standard_D2_v2"
            node_count = var.agent_count
            os_sku = "AzureLinux"
          linux_profile {
            admin_username = "azurelinux"
            ssh_key {
              key_data = file(var.ssh_public_key)
          network_profile {
            network_plugin    = "kubenet"
            load_balancer_sku = "standard"
          service_principal {
            client_id     = var.aks_service_principal_app_id
            client_secret = var.aks_service_principal_client_secret

    Similarly, you can specify the Azure Linux os_sku in azurerm_kubernetes_cluster_node_pool.

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

        variable "agent_count" {
            default = 3
        # The following two variable declarations are placeholder references.
        # Set the values for these variable in terraform.tfvars
        variable "aks_service_principal_app_id" {
          default = ""
        variable "aks_service_principal_client_secret" {
          default = ""
        variable "cluster_name" {
          default = "k8stest"
        variable "dns_prefix" {
          default = "k8stest"
        # Refer to https://azure.microsoft.com/global-infrastructure/services/?products=monitor for available Log Analytics regions.
        variable "log_analytics_workspace_location" {
          default = "eastus"
        variable "log_analytics_workspace_name" {
          default = "testLogAnalyticsWorkspaceName"
        # Refer to https://azure.microsoft.com/pricing/details/monitor/ for Log Analytics pricing
        variable "log_analytics_workspace_sku" {
          default = "PerGB2018"
        variable "resource_group_location" {
          default     = "eastus"
          description = "Location of the resource group."
        variable "resource_group_name_prefix" {
          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 "ssh_public_key" {
          default = "~/.ssh/id_rsa.pub"
  5. Create a file named outputs.tf and insert the following code:

        output "client_certificate" {
          value     = azurerm_kubernetes_cluster.k8s.kube_config[0].client_certificate
          sensitive = true
        output "client_key" {
          value     = azurerm_kubernetes_cluster.k8s.kube_config[0].client_key
          sensitive = true
        output "cluster_ca_certificate" {
          value     = azurerm_kubernetes_cluster.k8s.kube_config[0].cluster_ca_certificate
          sensitive = true
        output "cluster_password" {
          value     = azurerm_kubernetes_cluster.k8s.kube_config[0].password
          sensitive = true
        output "cluster_username" {
          value     = azurerm_kubernetes_cluster.k8s.kube_config[0].username
          sensitive = true
        output "host" {
          value     = azurerm_kubernetes_cluster.k8s.kube_config[0].host
          sensitive = true
        output "kube_config" {
          value     = azurerm_kubernetes_cluster.k8s.kube_config_raw
          sensitive = true
        output "resource_group_name" {
          value = azurerm_resource_group.rg.name
  6. Create a file named terraform.tfvars and insert the following code:

        aks_service_principal_app_id = "<service_principal_app_id>"
        aks_service_principal_client_secret = "<service_principal_password>"

Initialize Terraform and create an execution plan

  1. Initialize Terraform and download the Azure modules required to manage your Azure resources using the terraform init command.

    terraform init
  2. Create a Terraform execution plan using the terraform plan command.

    terraform plan -out main.tfplan

    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.

    To read more about persisting execution plans and security, see the security warnings.

  3. Apply the Terraform execution plan using the terraform apply command.

    terraform apply main.tfplan

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

Verify the results

  1. Get the resource group name using the following echo command.

    echo "$(terraform output resource_group_name)"
  2. Browse to the Azure portal.

  3. Under Azure services, select Resource groups and locate your new resource group to see the following resources created in this demo:

    • Solution: By default, the demo names this solution ContainerInsights. The portal shows the solution's workspace name in parenthesis.
    • Kubernetes service: By default, the demo names this service k8stest. (A managed Kubernetes cluster is also known as an AKS/Azure Kubernetes Service.)
    • Log Analytics Workspace: By default, the demo names this workspace with a prefix of TestLogAnalyticsWorkspaceName- followed by a random number.
  4. Get the Kubernetes configuration from the Terraform state and store it in a file that kubectl can read using the following echo command.

    echo "$(terraform output kube_config)" > ./azurek8s
  5. Verify the previous command didn't add an ASCII EOT character using the following cat command.

    cat ./azurek8s

    If you see << EOT at the beginning and EOT at the end, remove these characters from the file. Otherwise, you could receive the following error message: error: error loading config file "./azurek8s": yaml: line 2: mapping values are not allowed in this context.

  6. Set an environment variable so kubectl picks up the correct config using the following export command.

    export KUBECONFIG=./azurek8s
  7. Verify the health of the cluster using the kubectl get nodes command.

    kubectl get nodes

    When the Azure Linux Container Host cluster was created, monitoring was enabled to capture health metrics for both the cluster nodes and pods. These health metrics are available in the Azure portal. For more information on container health monitoring, see Monitor Azure Kubernetes Service health.

    Several key values were output when you applied the Terraform execution plan. For example, the host address, Azure Linux Container Host cluster username, and Azure Linux Container Host cluster password are output.

    To view all of the output values, run terraform output. To view a specific output value, run echo "$(terraform output <output_value_name>)".

Clean up resources

Delete AKS resources

When you no longer need the resources created with Terraform, you can remove them using the following steps.

  1. Run the terraform plan command and specify the destroy flag.

    terraform plan -destroy -out main.destroy.tfplan
  2. Remove the execution plan using the terraform apply command.

    terraform apply main.destroy.tfplan

Delete service principal


Delete the service principal you used in this demo only if you're not using it for anything else.

  1. Get the object ID of the service principal using the az ad sp list command

    az ad sp list --display-name "<display_name>" --query "[].{\"Object ID\":id}" --output table
  2. Delete the service principal using the az ad sp delete command.

    az ad sp delete --id <service_principal_object_id>

Troubleshoot Terraform on Azure

Troubleshoot common problems when using Terraform on Azure.

Next steps

In this quickstart, you deployed an Azure Linux Container Host cluster. To learn more about the Azure Linux Container Host and walk through a complete cluster deployment and management example, continue to the Azure Linux Container Host tutorial.