Kubernetes in Space - Azure

Brendan Thompson • 21 April 2021 • 11 min read

This is the first installment of a 3 (potentially 4) part series around deploying Kubernetes (k8s) to the major public clouds, the other posts will show how to deploy k8s on GCP and AWS. Once they've been posted I will update this post to ensure there are links out to those articles.

The first part of the blog post "Kubernetes in Space" is a little clickbaity but it is just something that resonates with me at the moment. There is a lot of drive with Cloud Native technology and consuming public clouds native PaaS offerings and I think we are losing some of the joy and certainly flexibility when it comes to consuming those. As a solution to this I personally prefer to use k8s where ever possible. It does, however, raise some other problems wherein organizations occasionally will try and push really nasty old COTS applications into k8s, which for anyway who has spent any time doing this knows that seldom does that work out well.

Enough of my ranting, and on with the post.

Table of Contents


Before we can learn how to deploy k8s, or in Azure's instance Azure Kubernetes Services (AKS) we must first understand the requirements, and components that are involved with deploying this service.

At a very high level the below is a list of things that are required in order to deploy AKS.

When AKS itself is deployed it will created a managed resource group in which the clusters resources will be deployed, those resources are:

This below diagram shows each of the components discussed above, and where they sit within Azure.

Azure Kubernetes Services Architecture

It is also important to note that there are different types of AKS clusters, they are as follows:

Infrastructure as Code#

Now that we have an understanding of how AKS works -at a high level- on Azure we can begin our journey into deploying it, the first step being to write the infrastructure as code (IAC).

I will organize this section into each of the terraform files that we will create in order to deploy the cluster. In the below code fence is a tree of the files that we are going to be looking at.

├── backend.tf
├── main.tf
├── network.tf
├── providers.tf
└── variables.tf

1. Backend#

The backend is the terraform file that instructs terraform which workspace and TFE/C instance to store state in.

terraform {
  backend "remote" {
    organization = "ministry-of-magic"

    workspaces {
      name = "k8s-azure"

As can be seen above we are working with the ministry-of-magic Terraform Cloud instance, and our workspace is called k8s-azure.

2. Providers#

The providers.tf file is where we store our requirements for the providers we are going to be consuming with the rest of our terraform code. I have opted to keep in the Service Principal details just to demonstrate which fields are going to be required.

terraform {
  required_providers {
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "=2.56.0"

provider "azurerm" {
  features {}

  subscription_id = ""
  client_id       = ""
client_secret = var.client_secret
tenant_id = "" }

There are two key sections within this file:

  1. terraform { required_providers {} } - Defines the providers that are going to be used within the code and any constraints around required versions for the providers that are going to be used. As can be seen above we are going to be consuming the azurerm provider, and we are constraining it to consume the 2.52.0 version of the provider.
  2. provider "azurerm {} - Configures the provider itself, in this instance we are passing in the authentication details, as well as a required field called features with an empty map.

One additional point here is that on the marked line we are consuming a variable to get the value for the client_secret. Depending on how you decide to configure the provider using the variable here might be redundant. The azurerm provider allows for all of its authentication details to be passed in as environment variables, meaning that this can simply set on the workspace itself.

3. Variables#

The variables.tf file is where the input variables that are required for the code to execute are to be defined.

variable "client_secret" {
  type        = string
  description = "Azure service principal client secret"

variable "environment" {
  type        = string
  description = "The environment the resources are deployed to"
  default     = "dev"

  validation {
condition = can(regex("", var.environment))
error_message = "Supplied environment does not allowed values."

We are declaring two input variables:

  1. client_secret - The client secret value that is to be consumed by the provider block.
  2. environment - An environment so that we can potentially create logic that will deploy things in different ways depending on if it's a production deployment or not. It is important to note that the highlighted lines in the variables file are to validate that the value we pass in for the variable matches a given regex. Further to this we have also set a default value for this input variable meaning that it is optional to be passed in at runtime.

4. Network#

The network.tf is where we will declare all the networking components. For such a simple deployment of AKS we will only be describing two resources.

resource "azurerm_virtual_network" "this" {
  name                = format("vn-aus-%s-k8s", var.environment)
  resource_group_name = azurerm_resource_group.this.name
  location            = azurerm_resource_group.this.location
  address_space       = [""]

  tags = {
    environment = var.environment

resource "azurerm_subnet" "node_pool" {
  name                 = format("sn-aus-%s-k8s-nodepool", var.environment)
  resource_group_name  = azurerm_resource_group.this.name
  virtual_network_name = azurerm_virtual_network.this.name
  address_prefixes     = [""]

As stated previously in this file we are only talking about two resources, they are:

  1. azurerm_virtual_network - The virtual network (vnet) where our AKS cluster will exist, the reason we are having to define this is because we will be deploy a CNI enabled AKS cluster. Note we have tagged this resource with the environment.
  2. azurerm_subnet - The subnet that the cluster's network resources will attach to.

5. Main#

main.tf is where all the juicy stuff lives, although due to the simplicity of this deployment it is only going to be two resources.

resource "azurerm_resource_group" "this" {
  name     = format("rg-aus-%s-k8s", var.environment)
  location = "australiasoutheast"

  tags = {
    environment = var.environment

resource "azurerm_kubernetes_cluster" "this" {
  name                = format("aks-aus-%s-k8s", var.environment)
  resource_group_name = azurerm_resource_group.this.name
  location            = azurerm_resource_group.this.location
  dns_prefix          = "blt"
  node_resource_group = format("%s-aks", azurerm_resource_group.this.name)

  default_node_pool {
    name           = "default"
    node_count     = 1
    vm_size        = "Standard_D2_v2"
    vnet_subnet_id = azurerm_subnet.node_pool.id

  identity {
    type = "SystemAssigned"

  network_profile {
    network_plugin     = "azure"
    network_policy     = "calico"
    service_cidr       = ""
    dns_service_ip     = ""
    docker_bridge_cidr = ""

  addon_profile {
    kube_dashboard {
      enabled = false

  tags = {
    environment = var.environment

The two resources we are going to be working with are:


Now that we have all our IAC together we can put that all together and deploy ourselves a sweet AKS cluster. This process is pretty straight forward!

In the example I have opted to use an API-driven workspace as this will give the flexibility I need/want to kick this off quickly.

From where ever your terraform code is residing you will need to run the basic terraform commands as follows:

  1. First we must initialize our working directory
terraform init
  1. Now we will quick of a plan to make sure everything looks the way we are expecting it to
terraform plan
  1. After reviewing the plan to ensure that it looks correct we will apply the run
terraform apply

When prompted to ensure to confirm the apply so that the resources themselves are built.

Once everything is green from your terminal we can go and checkout the cluster in the portal. From your subscriptions resource group view you should see something similar to the below:

Azure Portal Overview

As you can see we have three resource groups, the first is an Azure special one for monitoring the networks the other two are the ones that we created through our code! Now we have ourselves an AKS cluster in our subscription. Lets go dig into the two resource groups. This first image shows the contents of the resource group we actually created through our IAC, it contains -as we expect- two resources; an AKS cluster, and a Virtual Network.

Azure Portal Core Resource Group Overview

The second resource is the managed resource group, this is what is created by the AKS resource itself and managed by Microsoft. It is absolute best practice not to touch anything within the RG.

Azure Portal Managed Resource Group Overview

Now that all our resources have been deployed by TFE/C it will now be possible to deploy your containerised workloads into the AKS cluster.

Closing Thoughts#

Hopefully this first post has given some insight into how simple it is to deploy managed kubernetes clusters to Azure. It wasn't always this way either, Azure has had rather a few pittfalls when it came to Azure but they are steadily improving there offering and getting pretty close to their primary competitors.

If your organisation is running in Azure and you're looking for to use kubernetes, I would say that it is well worth checking out AKS as long as you do not have the requirement for fully private clusters. Microsoft's private link solution I feel is still rather brittle I hope its something they invest some more time into as it will make the offer far more compelling for larger and/or regulated organizations.

If there are any gaps, or anything further you'd like me to touch on please feel free to reach out.

Brendan Thompson

Principal Cloud Engineer

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