Some months ago a customer asked me if there was a way to deploy a Windows node pool with spot virtual machines and ephemeral disks in Azure Kubernetes Service (AKS).
The idea was to create a cluster that could be used to run Windows batch workloads and minimize costs by deploying the following:
- An AKS cluster with 2 linux nodes and ephemeral disks as the default node pool configuration.
- A Windows node pool with Spot Virtual Machines, ephemeral disks and auto-scaling enabled.
- Set the windows node pool minimum count and initial number of nodes set to 0.
To create a cluster with the desired configuration with terraform, follow the steps below:
Define the terraform providers to use
Create a providers.tf file with the following contents:
terraform {
required_version = "> 0.12"
required_providers {
azurerm = {
source = "azurerm"
version = "~> 2.26"
}
}
}
provider "azurerm" {
features {}
}
Define the variables
Create a variables.tf file with the following contents:
variable "resource_group_name" {
default = "aks-win"
}
variable "location" {
default = "West Europe"
}
variable "cluster_name" {
default = "aks-win"
}
variable "dns_prefix" {
default = "aks-win"
}
Define the resource group
Create a main.tf file with the following contents:
# Create Resource Group
resource "azurerm_resource_group" "rg" {
name = var.resource_group_name
location = var.location
}
Define the VNET for the cluster
Create a vnet-server.tf file with the following contents:
resource "azurerm_virtual_network" "vnet" {
name = "aks-vnet"
location = azurerm_resource_group.rg.location
resource_group_name = azurerm_resource_group.rg.name
address_space = ["10.0.0.0/16"]
}
resource "azurerm_subnet" "aks-subnet" {
name = "aks-subnet"
resource_group_name = azurerm_resource_group.rg.name
virtual_network_name = azurerm_virtual_network.vnet.name
address_prefixes = ["10.0.1.0/24"]
}
Define the AKS cluster
Create a aks-server.tf file with the following contents:
# Deploy Kubernetes
resource "azurerm_kubernetes_cluster" "k8s" {
name = var.cluster_name
location = azurerm_resource_group.rg.location
resource_group_name = azurerm_resource_group.rg.name
dns_prefix = var.dns_prefix
default_node_pool {
name = "default"
node_count = 2
vm_size = "Standard_D2s_v3"
os_disk_size_gb = 30
os_disk_type = "Ephemeral"
vnet_subnet_id = azurerm_subnet.aks-subnet.id
max_pods = 15
enable_auto_scaling = false
}
# Using Managed Identity
identity {
type = "SystemAssigned"
}
network_profile {
# The --service-cidr is used to assign internal services in the AKS cluster an IP address. This IP address range should be an address space that isn't in use elsewhere in your network environment, including any on-premises network ranges if you connect, or plan to connect, your Azure virtual networks using Express Route or a Site-to-Site VPN connection.
service_cidr = "172.0.0.0/16"
# The --dns-service-ip address should be the .10 address of your service IP address range.
dns_service_ip = "172.0.0.10"
# The --docker-bridge-address lets the AKS nodes communicate with the underlying management platform. This IP address must not be within the virtual network IP address range of your cluster, and shouldn't overlap with other address ranges in use on your network.
docker_bridge_cidr = "172.17.0.1/16"
network_plugin = "azure"
network_policy = "calico"
}
role_based_access_control {
enabled = true
}
addon_profile {
kube_dashboard {
enabled = false
}
}
}
resource "azurerm_kubernetes_cluster_node_pool" "windows" {
kubernetes_cluster_id = azurerm_kubernetes_cluster.k8s.id
name = "win"
priority = "Spot"
eviction_policy = "Delete"
spot_max_price = -1 # The VMs will not be evicted for pricing reasons.
os_type = "Windows"
# "The virtual machine size Standard_D2s_v3 has a cache size of 53687091200 bytes, but the OS disk requires 137438953472 bytes. Use a VM size with larger cache or disable ephemeral OS."
# https://docs.microsoft.com/en-us/azure/virtual-machines/ephemeral-os-disks#size-requirements
vm_size = "Standard_DS3_v2"
os_disk_type = "Ephemeral"
node_count = 0
enable_auto_scaling = true
max_count = 3
min_count = 0
}
data "azurerm_resource_group" "node_resource_group" {
name = azurerm_kubernetes_cluster.k8s.node_resource_group
}
# Assign the Contributor role to the AKS kubelet identity
resource "azurerm_role_assignment" "kubelet_contributor" {
scope = data.azurerm_resource_group.node_resource_group.id
role_definition_name = "Contributor" #"Virtual Machine Contributor"?
principal_id = azurerm_kubernetes_cluster.k8s.kubelet_identity[0].object_id
}
resource "azurerm_role_assignment" "kubelet_network_contributor" {
scope = azurerm_virtual_network.vnet.id
role_definition_name = "Network Contributor"
principal_id = azurerm_kubernetes_cluster.k8s.identity[0].principal_id
}
Deploy the AKS cluster
Run:
terraform init
terraform apply
Get the credentials for the cluster:
RESOURCE_GROUP="aks-win"
CLUSTER_NAME="aks-win"
az aks get-credentials --resource-group $RESOURCE_GROUP --name $CLUSTER_NAME
To verify that there are no windows VMs running, execute:
kubectl get nodes
you should see something like:
NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME
aks-default-36675761-vmss000000 Ready agent 80m v1.20.9 10.0.1.4 <none> Ubuntu 18.04.5 LTS 5.4.0-1056-azure containerd://1.4.8+azure
aks-default-36675761-vmss000001 Ready agent 80m v1.20.9 10.0.1.20 <none> Ubuntu 18.04.5 LTS 5.4.0-1056-azure containerd://1.4.8+azure
Deploy a Windows workload:
To deploy a Windows workload, create a windows_deployment.yaml file with the following contents:
apiVersion: apps/v1
kind: Deployment
metadata:
name: servercore
labels:
app: servercore
spec:
replicas: 1
template:
metadata:
name: servercore
labels:
app: servercore
spec:
nodeSelector:
"kubernetes.azure.com/scalesetpriority": "spot"
containers:
- name: servercore
image: mcr.microsoft.com/dotnet/framework/samples:aspnetapp
resources:
limits:
cpu: 1
memory: 800M
requests:
cpu: .1
memory: 150M
ports:
- containerPort: 80
tolerations:
- key: "kubernetes.azure.com/scalesetpriority"
operator: "Equal"
value: "spot"
effect: "NoSchedule"
selector:
matchLabels:
app: servercore
and deploy it to your cluster:
kubectl apply -f windows_deployment.yaml
Note the following:
- The kubernetes.azure.com/scalesetpriority label is used to ensure that the workload is scheduled on a spot node.
- tolerations are used to ensure that the workload is scheduled on a spot node.
- Deployment will take a while (> 5 minutes) since the windows pool must scale up to fullfill the request.
Now check the nodes again:
kubectl get nodes
this time you should see something like:
NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME
aks-default-36675761-vmss000000 Ready agent 91m v1.20.9 10.0.1.4 <none> Ubuntu 18.04.5 LTS 5.4.0-1056-azure containerd://1.4.8+azure
aks-default-36675761-vmss000001 Ready agent 91m v1.20.9 10.0.1.20 <none> Ubuntu 18.04.5 LTS 5.4.0-1056-azure containerd://1.4.8+azure
akswin000000 Ready agent 102s v1.20.9 10.0.1.36 <none> Windows Server 2019 Datacenter 10.0.17763.2114 docker://20.10.6
If you check the pod events you’ll find that the workload triggered a scale up:
kubectl describe $(kubectl get po -l "app=servercore" -o name)
I’ll let you test what happens if you delete the deployment.
Hope it helps!!!
Please find the complete terraform configuration here
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