k8s: Terraform deployment for Azure clusters

This provides a Terraform configuration for deploying our Kubernetes
clusters to Azure. We deploy an identical cluster to each of a list of
regions, with one small node for admin purposes due to a requirement to
not use spot instances for the main node group for the and two
autoscaling groups one with small 8 core nodes for most jobs and one
with bigger nodes for the more resource intensive ones.

This is different to our current scheme where each cluster has a single
node group and we direct jobs in Jenkins. With this scheme we allow the
Kubernetes scheduler to place jobs, or we can still direct them to
specific node sizes using nodeSelector in the jobs and the labels that
are assigned to the nodegroups. This is a more Kubernetes way of doing
things and decouples further from Jenkins.

Signed-off-by: Mark Brown <[email protected]>

k8s/azure/README

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+This needs to be run on a machine with Terraform install and the
+Azure CLI.  Personal login for the Azure CLI can be done with:
+
+	az login
+
+The actual account used is a service principal account though:
+
+	az ad sp create-for-rbac -n kernelci-k8s
+
+which outputs an appId and password, this should be distributed via the
+credential store and set in terraform variables, see variables.tf.
+
+When the clusters are created a logged in user can set up the client
+credentials like this:
+
+	for c in $(az aks list --query '[].name' -o tsv) ; do
+		az aks get-credentials --resource-group kernelci-workers --name ${c}
+	done
+
+(TBD: also put this in outputs.tf, need to figure out syntax for arrays)

k8s/azure/aks-cluster.tf

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+# Store the terraform state in cloud storage rather than just the
+# current directory, terraform supports Azure blob storage directly.
+# This means configuration doesn't need to be on a single machine
+# somewhere.
+#
+# See https://www.terraform.io/language/settings/backends/azurerm
+#
+terraform {
+  backend "azurerm" {
+    resource_group_name  = "kernelci-tf-storage"
+    storage_account_name = "kernelci-tf"
+    container_name       = "tfstate"
+    key                  = "workers.terraform.tfstate"
+  }
+}
+
+provider "azurerm" {
+  features {}
+}
+
+# We assign all clusters to the same resource group, this is purely for
+# accounting purposes so it doesn't matter where the resource group is
+resource "azurerm_resource_group" "workers" {
+  name     = "kernelci-workers"
+  location = "East US"
+
+  tags = {
+    environment = "kernelci-workers"
+  }
+}
+
+locals {
+  zones = toset([
+    "francecentral",
+    "uksouth",
+    "eastus2",
+  ])
+}
+
+resource "azurerm_kubernetes_cluster" "workers" {
+  for_each = local.zones
+
+  name                = "${each.key}-workers-aks"
+  location            = each.key
+  resource_group_name = azurerm_resource_group.workers.name
+  dns_prefix          = "${each.key}-workers-k8s"
+
+  # Automatically roll out upgrades from AKS
+  automatic_channel_upgrade = "stable"
+
+  # Single always present node as AKS requires a default node pool -
+  # Terraform and/or AKS don't let us tag this as a spot instance and
+  # ideally we can scale the builders down to 0 so this is a small
+  # instance not tagged for work.
+  default_node_pool {
+    name            = "default"
+    node_count      = 1
+    vm_size         = "Standard_DS2_v2"
+    os_disk_size_gb = 30
+
+    node_labels = {
+      "kernelci/management" = "management"
+    }
+  }
+
+  service_principal {
+    client_id     = var.appId
+    client_secret = var.password
+  }
+
+  role_based_access_control {
+    enabled = true
+  }
+
+  tags = {
+    environment = "kernelci"
+  }
+}
+
+# Smaller nodes for most jobs
+resource "azurerm_kubernetes_cluster_node_pool" "small_workers" {
+  for_each = azurerm_kubernetes_cluster.workers
+
+  name = "smallworkers"
+  kubernetes_cluster_id = each.value.id
+
+  # 3rd gen Xeon 8 cores, 32G RAM - general purpose
+  vm_size               = "Standard_D8s_v5"
+
+  # Currently things struggle with scale to 0 so require a node
+  enable_auto_scaling = true
+  min_count  = 1
+  node_count = 1
+  max_count  = 10
+
+  priority = "Spot"
+  # We could set this lower to control costs, -1 means up to on demand
+  # price
+  spot_max_price = -1
+
+  node_labels = {
+    "kernelci/worker" = "worker"
+    "kernelci/worker-size" = "small"
+  }
+}
+
+# Big nodes for more intensive jobs (and large numbers of small jobs)
+resource "azurerm_kubernetes_cluster_node_pool" "big_workers" {
+  for_each = azurerm_kubernetes_cluster.workers
+
+  name = "bigworkers"
+  kubernetes_cluster_id = each.value.id
+
+  # 3rd gen Xeon, 32 core, 64G RAM - compute optimised
+  vm_size               = "Standard_F32s_v2"
+
+  # Currently things struggle with scale to 0 so require a node
+  enable_auto_scaling = true
+  min_count  = 1
+  node_count = 1
+  max_count  = 10
+
+  priority = "Spot"
+  # We could set this lower to control costs, -1 means up to on demand
+  # price
+  spot_max_price = -1
+
+  node_labels = {
+    "kernelci/worker" = "worker"
+    "kernelci/worker-size" = "big"
+  }
+}

k8s/azure/outputs.tf

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+output "resource_group_name" {
+  value = azurerm_resource_group.workers.name
+}

k8s/azure/variables.tf

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+variable "appId" {
+  description = "Azure Kubernetes Service Cluster service principal"
+}
+
+variable "password" {
+  description = "Azure Kubernetes Service Cluster password"
+}

k8s/azure/versions.tf

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+terraform {
+  required_providers {
+    azurerm = {
+      source  = "hashicorp/azurerm"
+      version = "2.66.0"
+    }
+  }
+
+  required_version = ">= 0.14"
+}
+