In this tutorial, we'll create a Kubernetes v1.23.3 cluster on Google Compute Engine with Flatcar Linux.
We'll declare a Kubernetes cluster using the Typhoon Terraform module. Then apply the changes to create a network, firewall rules, health checks, controller instances, worker managed instance group, load balancers, and TLS assets.
Controller hosts are provisioned to run an etcd-member
peer and a kubelet
service. Worker hosts run a kubelet
service. Controller nodes run kube-apiserver
, kube-scheduler
, kube-controller-manager
, and coredns
, while kube-proxy
and calico
(or flannel
) run on every node. A generated kubeconfig
provides kubectl
access to the cluster.
- Google Cloud Account and Service Account
- Google Cloud DNS Zone (registered Domain Name or delegated subdomain)
- Terraform v0.13.0+
Install Terraform v0.13.0+ on your system.
$ terraform version
Terraform v1.0.0
Read concepts to learn about Terraform, modules, and organizing resources. Change to your infrastructure repository (e.g. infra
).
cd infra/clusters
Login to your Google Console API Manager and select a project, or signup if you don't have an account.
Select "Credentials" and create a service account key. Choose the "Compute Engine Admin" and "DNS Administrator" roles and save the JSON private key to a file that can be referenced in configs.
mv ~/Downloads/project-id-43048204.json ~/.config/google-cloud/terraform.json
Configure the Google Cloud provider to use your service account key, project-id, and region in a providers.tf
file.
provider "google" {
project = "project-id"
region = "us-central1"
credentials = file("~/.config/google-cloud/terraform.json")
}
provider "ct" {}
terraform {
required_providers {
ct = {
source = "poseidon/ct"
version = "0.9.1"
}
google = {
source = "hashicorp/google"
version = "4.7.0"
}
}
}
Additional configuration options are described in the google
provider docs.
!!! tip
Regions are listed in docs or with gcloud compute regions list
. A project may contain multiple clusters across different regions.
Define a Kubernetes cluster using the module google-cloud/flatcar-linux/kubernetes
.
module "yavin" {
source = "git::https://github.com/poseidon/typhoon//google-cloud/flatcar-linux/kubernetes?ref=v1.23.3"
# Google Cloud
cluster_name = "yavin"
region = "us-central1"
dns_zone = "example.com"
dns_zone_name = "example-zone"
# configuration
ssh_authorized_key = "ssh-rsa AAAAB3Nz..."
# optional
worker_count = 2
}
Reference the variables docs or the variables.tf source.
Initial bootstrapping requires bootstrap.service
be started on one controller node. Terraform uses ssh-agent
to automate this step. Add your SSH private key to ssh-agent
.
ssh-add ~/.ssh/id_rsa
ssh-add -L
Initialize the config directory if this is the first use with Terraform.
terraform init
Plan the resources to be created.
$ terraform plan
Plan: 64 to add, 0 to change, 0 to destroy.
Apply the changes to create the cluster.
$ terraform apply
module.yavin.null_resource.bootstrap: Still creating... (10s elapsed)
...
module.yavin.null_resource.bootstrap: Still creating... (5m30s elapsed)
module.yavin.null_resource.bootstrap: Still creating... (5m40s elapsed)
module.yavin.null_resource.bootstrap: Creation complete (ID: 5768638456220583358)
Apply complete! Resources: 62 added, 0 changed, 0 destroyed.
In 4-8 minutes, the Kubernetes cluster will be ready.
Install kubectl on your system. Obtain the generated cluster kubeconfig
from module outputs (e.g. write to a local file).
resource "local_file" "kubeconfig-yavin" {
content = module.yavin.kubeconfig-admin
filename = "/home/user/.kube/configs/yavin-config"
}
List nodes in the cluster.
$ export KUBECONFIG=/home/user/.kube/configs/yavin-config
$ kubectl get nodes
NAME ROLES STATUS AGE VERSION
yavin-controller-0.c.example-com.internal <none> Ready 6m v1.23.3
yavin-worker-jrbf.c.example-com.internal <none> Ready 5m v1.23.3
yavin-worker-mzdm.c.example-com.internal <none> Ready 5m v1.23.3
List the pods.
$ kubectl get pods --all-namespaces
NAMESPACE NAME READY STATUS RESTARTS AGE
kube-system calico-node-1cs8z 2/2 Running 0 6m
kube-system calico-node-d1l5b 2/2 Running 0 6m
kube-system calico-node-sp9ps 2/2 Running 0 6m
kube-system coredns-1187388186-dkh3o 1/1 Running 0 6m
kube-system coredns-1187388186-zj5dl 1/1 Running 0 6m
kube-system kube-apiserver-controller-0 1/1 Running 0 6m
kube-system kube-controller-manager-controller-0 1/1 Running 0 6m
kube-system kube-proxy-117v6 1/1 Running 0 6m
kube-system kube-proxy-9886n 1/1 Running 0 6m
kube-system kube-proxy-njn47 1/1 Running 0 6m
kube-system kube-scheduler-controller-0 1/1 Running 0 6m
Learn about maintenance and addons.
Check the variables.tf source.
Name | Description | Example |
---|---|---|
cluster_name | Unique cluster name (prepended to dns_zone) | "yavin" |
region | Google Cloud region | "us-central1" |
dns_zone | Google Cloud DNS zone | "google-cloud.example.com" |
dns_zone_name | Google Cloud DNS zone name | "example-zone" |
ssh_authorized_key | SSH public key for user 'core' | "ssh-rsa AAAAB3NZ..." |
Check the list of valid regions and list Container Linux images with gcloud compute images list | grep coreos
.
Clusters create a DNS A record ${cluster_name}.${dns_zone}
to resolve a TCP proxy load balancer backed by controller instances. This FQDN is used by workers and kubectl
to access the apiserver(s). In this example, the cluster's apiserver would be accessible at yavin.google-cloud.example.com
.
You'll need a registered domain name or delegated subdomain on Google Cloud DNS. You can set this up once and create many clusters with unique names.
resource "google_dns_managed_zone" "zone-for-clusters" {
dns_name = "google-cloud.example.com."
name = "example-zone"
description = "Production DNS zone"
}
!!! tip "" If you have an existing domain name with a zone file elsewhere, just delegate a subdomain that can be managed on Google Cloud (e.g. google-cloud.mydomain.com) and update nameservers.
Name | Description | Default | Example |
---|---|---|---|
controller_count | Number of controllers (i.e. masters) | 1 | 3 |
worker_count | Number of workers | 1 | 3 |
controller_type | Machine type for controllers | "n1-standard-1" | See below |
worker_type | Machine type for workers | "n1-standard-1" | See below |
os_image | Flatcar Linux image for compute instances | "flatcar-stable" | flatcar-stable, flatcar-beta, flatcar-alpha |
disk_size | Size of the disk in GB | 30 | 100 |
worker_preemptible | If enabled, Compute Engine will terminate workers randomly within 24 hours | false | true |
controller_snippets | Controller Container Linux Config snippets | [] | example |
worker_snippets | Worker Container Linux Config snippets | [] | example |
networking | Choice of networking provider | "cilium" | "calico" or "cilium" or "flannel" |
pod_cidr | CIDR IPv4 range to assign to Kubernetes pods | "10.2.0.0/16" | "10.22.0.0/16" |
service_cidr | CIDR IPv4 range to assign to Kubernetes services | "10.3.0.0/16" | "10.3.0.0/24" |
worker_node_labels | List of initial worker node labels | [] | ["worker-pool=default"] |
Check the list of valid machine types.
Add worker_preemptible = "true"
to allow worker nodes to be preempted at random, but pay significantly less. Clusters tolerate stopping instances fairly well (reschedules pods, but cannot drain) and preemption provides a nice reward for running fault-tolerant cluster systems.`