The journey of my "cloud" infrastructure; What I learned about terraform

servers-stuff devops virtualization

Proceeding with caution is advised

This article purely reflects my opinions and should not be used to draw conclusions about the benefits and disadvantages of the technologies that will be mentioned. By no means the information and methodologies presented in this article are at a professional level, as such the article might contain mild to vast amounts of hacks and bodging. Do proceed with care.

My journey in self-hosted world


My journey in the self-hosted world has started in 2016, after having a summer job, I got enough money to buy a second hand server - which at that time I had been planning for a while. Not knowing better, the first hypervisor software I had used was Proxmox. However, I had only used Proxmox as means to create containers, and not virtual machines. For a long while, Proxmox has been good enough for my needs. As I was getting into the habit of keeping my computer with the latest and greatest kernel version, I had realised that the Debian - the distribution on which Proxmox is based - was not cutting it.

In between not finding a great way to perform backups for the container images on Proxmox and my burning desire to run Linux kernel version 5, I decided to switch to Fedora in combination with LXD (container management software).

During this whole time, I would manage all the containers and software manually, which was increasingly becoming more and more tedious as I wanted to perform updates more frequently.

As I didn’t discover Ansible and other automation software yet, I did what every programmer would do - turn to scripts to solve the issue. was the name of the script I used to run in order to update my system. The script itself was just executing the package manager update command in each container, by using LXD’s lxc exec command:

lxc exec container -- dnf update
# ... 

The dawn of DevOps era

In 2020, I had my final exams for high school and I had to study for them, during the period before the exams my server was sitting turned off waiting for me to take care of it. At the end of the summer, I had decided to take a break from the summer break to configure my servers a bit more seriously, as I was about to leave for university. I finally stopped procrastinating and sleeping on Ansible and a more DevOps flow for my server.

During this week, I wrote ansible yaml files to configure my “infrastructure” - the networking interfaces on the server and the containers, with properties (the networks the container is attached to, number of cores, ram size, disk storage quote) registered in the inventory file. On top of that, I wrote roles for a range of other things, including ssh servers, firewalld configurations, reverse proxy (I decided writing my own instead of using an already written one).

Everything was fine with my ansible until…

BTRFS disaster and the new age of Terraform

After a power outage at the location of the server, the BTRFS pool I was using for the container storage was left corrupt, with no way for me to recover it. This unfortunate corruption prompted me to make a change I wanted to do way before.

As I realized the Ansible role I created for creating containers wasn’t cutting it and that LXD had some funky things, I decided to instead become even more professional and use what the big boys use - Terraform. However, instead of using OpenStack or any other cloud provider, I wanted to use a KVM provider. While containers are great technology, working with LXD didn’t feel like it was an established piece of software (the fact that it’s only available on snapcraft in many distributions doesn’t help it either). Add the awkward configuration required to add remotes (I was planning on adding the ansible playbooks in a CI book all along) was not cutting it for me. As I was researching the options I would have to connect to the LXD containers from the CI, I had realized that I am better off with libvirt’s over ssh remoting. Not to mention the very great virt-manager tool, that shows my vms as a very nice list.

In between doing my coursework, I had spent some time playing with libvirt and terraform on my testing server, and when I became confident in my terraform code, I decided to roll the terraform configurations out to my “production” server. Everything went almost smoothly, except some cloudinit oddities, and some other configuration bugs I had in my ansible playbooks.

And… this is the present day, now my server is working fine, all containers were replaced with vms, the RAM consumption sky-rocketed - but I have enough RAM on the trusty second hand old server I bought - and everything in terms of VM creation is managed by Terraform. I will take the reminder of this post show you, dear reader, what I learned about Terraform, in the small amount of time I have been using it.

What I learned about Terraform

This section is not supposed to be a tutorial in and on itself, but rather an extension of tutorials on getting started with terraform and the libvirt provider.

Terraform is an “Infrastructure as Code” software tool. In layman’s terms, Infrastructure as Code means creating/managing infrastructure via means of a configuration language. These configuration languages, as far as I am aware, are usually descriptive languages, in this case being Terraform itself. In my case, what I needed from is a way for me to “declare” vms with a limited amount of configurability - CPU cores count, RAM, the network bridge the vm is attached to, the ip address or dhcp and the distribution of linux to be used. Since I am using KVM, I have decided to use the libvirt provider (providers are akin to modules, though they ‘provide’ resource types that can be defined).

A vm can be simply defined as a resource the following way:

resource "libvirt_domain" "vm-test" {
    name   = "vm-test"
    memory = "1024"
    vcpu   = 1

    cloudinit =

    network_interface {
        network_name = "default"

    console {
        type = "pty"
        target_port = "0"
        target_type = "serial"

    console {
        type = "pty"
        target_type = "virtio"
        target_port = "1"

    disk {
        volume_id =

    graphics {
        type = "spice"
        listen_type = "address"
        autoport = true

The block of code covers defining a resource of type libvirt_domain - domain being a vm, with the name of the resource being “vm-test” and the name of the vm itself being vm-test. I was a bit confused at first about the difference between the resource itself and the domain, however, as the language allows “loops”, one resource can keep track of multiple domains.

While the other options to set the vm up are rather clear, one noteworthy thing is the ability to reference other resources, in this case the cloudinit image and the disk image are referenced from other terraform resources. The libvirt provider allows the user to create several types of resources: pools (where the disk images are stored), disks, cloudinit disks, networks and domains.


Terraform’s looping mechanism will be the feature that I will use to achieve templating of the vm configuration. The way that looping works is kind of peculiar, however, not very different compared to Ansible.

In order to loop over an object, the terraform “abstract” resource itself provides a special option, called for_each, which can be used as follows:

resource "libvirt_domain" "domain-vms" {
    for_each = {for vm in var.vms: => vm}

    name =
    memory = each.value.memory
    vcpu = each.value.cpu


However there is a catch, considering how Terraform calculates the state of the resource itself and the changes it has to make to the infrastructure, the only objects that can be looped over are basically sets and dictionaries. In the previous example, the variable var.vms itself is a list, however, the construct {for vm in var.vms: => vm} loops over the list and creates a dictionary with pairs of a as a key and the vm object itself as value.

There are other ways to achieve iteration over a list, such as the toset function.

Input Variables

Input Variables are properties to a Terraform file that are defined in a different file that can be either a .tfvars file or a json file. These variables are special because each used variable needs to be declared by type. The declaration of the var.vms variable is as follows:

variable "vms" {
        name = string
        distro = string
        cpu = number
        memory = string
        storage = number
        networks = list(

A tfvars file looks as follows:

vms = [
        "name": "test",
        "distro": "base-fedora33",
        "cpu": 1,
        "memory": "1024",
        "storage": 5,
        "networks": [{
            "name": "test",
            "ip-address": "",
            "gateway": ""

In my case, an empty ip-address means that the ip is dynamically allocated.

The interesting aspect of Input Variables is that input checking can be done in the variable declaration block, however checking which I have not done.


cloud-init is a mechanism provided by Linux distributions in cloud images to be able to configure the image in a first boot, without requiring user intervention. The way that cloud images are set up in Terraform is by first declaring a data object that is going to be a generated template from the cloud-init configuration files:

data "template_file" "user_data" {
    for_each = {for vm in var.vms: => vm}

    template = templatefile("${path.module}/cloudinit/cloud_init.cfg", {name =, ssh_keys=var.authorized-ssh-keys})

data "template_file" "network_config" {
    for_each = local.vms_networks

    template = templatefile("${path.module}/cloudinit/network.cfg", {networks = each.value})

After which the cloud-init image resource itself is declared:

resource "libvirt_cloudinit_disk" "commoninit" {
    for_each = {for vm in var.vms: => vm}

    name = join("-", [, "commoninit.iso"])
    user_data = data.template_file.user_data[].rendered
    network_config = data.template_file.network_config[].rendered
    pool = "vm-pool"

The cloud-init I am using are looking as follows:



preserve_hostname: true
hostname: ${name}
 - [ ls, -l, / ]
 - [ sh, -xc, "echo $(date) ': hello world!'" ]
 - [ hostnamectl, set-hostname, "${name}" ]
ssh_pwauth: 0
disable_root: 1
  - name: alex
    groups: users, admin
    home: /home/alex
    shell: /bin/bash
    lock_passwd: true
      %{for key in ssh_keys ~}
- ${key}
      %{ endfor ~}

final_message: "The system is finally up, after $UPTIME seconds"

This is the main config file, and it is mainly concerned about setting up the hostname and the admin user with the ssh keys. However, in my quest, I have discovered a few gotchas with cloud-init: - the first line of the cloud_init.cfg file has to be #cloud-config - On the Fedora image, in particular, the module for setting up the hostname did not appear to work, as such, I had to resort to running a hostnamectl command to change the hostname of the vm.

The network.cfg file is a yaml file and looks as follows:

version: 2
  %{ for index, network in networks ~}
      macaddress: ${network.mac-address}
%{if network.ip-address == "" ~}
    dhcp4: true
%{else ~}
      - ${network.ip-address}/24
    gateway4: ${network.gateway}
        addresses: [${network.gateway}]
%{endif ~}
  %{ endfor ~}

This file is concerned about setting up the static IP address or a DHCP configuration for each network interface attached to the vm - more details are covered in the networking section.


My network is managed by a pfSense router, where I have created VLANs to separate the vms, by their job. On the server, a bridge for each VLAN is created then each vm is attached to the aforementioned bridge. As each VM can be attached to multiple VLANs, it is mandatory to create the configuration system to be able to manage multiple networking interface for each vm, each of the interface being configured with either a static ip or a dynamic ip.

Because I was not able to get the networking configuration of cloud-init to work nicely with trying to match the network cards by order, I have decided to use a mac address generator provider and assign each network interface with a well known mac address I can use in the cloud-init configuration.

One of the main hurdles I came across with the networking configuration is adding a dynamic number of interfaces to the domain, which can be done using the dynamic block as follows:

resource "libvirt_cloudinit_disk" "commoninit" {
    for_each = {for vm in var.vms: => vm}


    dynamic "network_interface" {
        for_each = local.vms_networks[]
            # local.vms_network is a variable that contains the network interface options (ip, the bridge it is attached to) 
            # and the generated MAC address.
        content {
            bridge = join("-", [network_interface.value["name"], "br"])
            mac = network_interface.value["mac-address"]
            hostname =


The bridge networks are configured to the host through NetworkManager, and they are defined to libvirt manually, as I have not managed to move the definitions in the terraform file yet.

The Sequel

The saga is not done yet, it rarely is. One of the biggest improvements I want to bring to my small “cloud” is to make it actually be managed entirely by Continuous Integration. Until now, I have done everything to move into that direction, however the main challenge will be creating a good backuping plan, to be able to backup everything before anything is changed by the Continuous Integration.

As this is one of the biggest next steps, there are lots of small steps that I want to implement - one of them being a DNS server maintained by Ansible. The reason why I need DHCP on some of the hosts is that it is the only way these hosts can be registered in pfSense’s DNS server. However, by swapping out all dynamic IPs for static ones and creating a DNS server pfSense can forward my local domains too, I will not need DHCP anymore, which overall would make management easier.