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# Kubernetes on GCP with Terraform
Provision a Kubernetes cluster on GCP using Terraform and Kubespray
## Overview
The setup looks like following
```text Kubernetes cluster +-----------------------+ +---------------+ | +--------------+ | | | | | +--------------+ | | API server LB +---------> | | | | | | | | | Master/etcd | | +---------------+ | | | node(s) | | | +-+ | | | +--------------+ | | ^ | | | | | v | +---------------+ | +--------------+ | | | | | +--------------+ | | Ingress LB +---------> | | | | | | | | | Worker | | +---------------+ | | | node(s) | | | +-+ | | | +--------------+ | +-----------------------+ ```
## Requirements
* Terraform 0.12.0 or newer
## Quickstart
To get a cluster up and running you'll need a JSON keyfile. Set the path to the file in the `tfvars.json` file and run the following:
```bash terraform apply -var-file tfvars.json -state dev-cluster.tfstate -var gcp_project_id=<ID of your GCP project> -var keyfile_location=<location of the json keyfile> ```
To generate kubespray inventory based on the terraform state file you can run the following:
```bash ./generate-inventory.sh dev-cluster.tfstate > inventory.ini ```
You should now have a inventory file named `inventory.ini` that you can use with kubespray, e.g.
```bash ansible-playbook -i contrib/terraform/gcs/inventory.ini cluster.yml -b -v ```
## Variables
### Required
* `keyfile_location`: Location to the keyfile to use as credentials for the google terraform provider * `gcp_project_id`: ID of the GCP project to deploy the cluster in * `ssh_pub_key`: Path to public ssh key to use for all machines * `region`: The region where to run the cluster * `machines`: Machines to provision. Key of this object will be used as the name of the machine * `node_type`: The role of this node *(master|worker)* * `size`: The size to use * `zone`: The zone the machine should run in * `additional_disks`: Extra disks to add to the machine. Key of this object will be used as the disk name * `size`: Size of the disk (in GB) * `boot_disk`: The boot disk to use * `image_name`: Name of the image * `size`: Size of the boot disk (in GB) * `ssh_whitelist`: List of IP ranges (CIDR) that will be allowed to ssh to the nodes * `api_server_whitelist`: List of IP ranges (CIDR) that will be allowed to connect to the API server * `nodeport_whitelist`: List of IP ranges (CIDR) that will be allowed to connect to the kubernetes nodes on port 30000-32767 (kubernetes nodeports) * `ingress_whitelist`: List of IP ranges (CIDR) that will be allowed to connect to ingress on ports 80 and 443
### Optional
* `prefix`: Prefix to use for all resources, required to be unique for all clusters in the same project *(Defaults to `default`)* * `master_sa_email`: Service account email to use for the control plane nodes *(Defaults to `""`, auto generate one)* * `master_sa_scopes`: Service account email to use for the control plane nodes *(Defaults to `["https://www.googleapis.com/auth/cloud-platform"]`)* * `master_preemptible`: Enable [preemptible](https://cloud.google.com/compute/docs/instances/preemptible) for the control plane nodes *(Defaults to `false`)* * `master_additional_disk_type`: [Disk type](https://cloud.google.com/compute/docs/disks/#disk-types) for extra disks added on the control plane nodes *(Defaults to `"pd-ssd"`)* * `worker_sa_email`: Service account email to use for the worker nodes *(Defaults to `""`, auto generate one)* * `worker_sa_scopes`: Service account email to use for the worker nodes *(Defaults to `["https://www.googleapis.com/auth/cloud-platform"]`)* * `worker_preemptible`: Enable [preemptible](https://cloud.google.com/compute/docs/instances/preemptible) for the worker nodes *(Defaults to `false`)* * `worker_additional_disk_type`: [Disk type](https://cloud.google.com/compute/docs/disks/#disk-types) for extra disks added on the worker nodes *(Defaults to `"pd-ssd"`)*
An example variables file can be found `tfvars.json`
## Known limitations
This solution does not provide a solution to use a bastion host. Thus all the nodes must expose a public IP for kubespray to work.
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