Multi-Cloud Deployments with Terraform and Packer

Updated on Oct. 3, 2023, 6:42 a.m., by: sbmagar

## Terraform and Packer

With the rise of cloud computing, many organizations are adopting multi-cloud strategies to increase the availability and redundancy of their applications. However, managing multiple cloud providers can be a daunting task. This is where HashiCorp Terraform and Packer come in. Terraform is an infrastructure-as-code tool that allows you to define and manage your cloud infrastructure in a declarative way. Packer is a tool for creating machine images for multiple platforms in a repeatable and consistent way. In this blog post, we will explore how to use Terraform and Packer to create multi-cloud deployments.

## **Prerequisites**

Before you begin creating multi-cloud deployments with Terraform and Packer, you should have:

- An understanding of cloud computing and multi-cloud strategies
- Familiarity with at least one cloud provider (e.g. AWS, Azure, Google Cloud)
- Familiarity with infrastructure-as-code concepts
- Experience with the command line

## Multi-Cloud Deployments with HashiCorp Terraform and Packer

### Example 1: Multi-Cloud Deployment with AWS and Azure

Imagine that you need to deploy a web application that should be available on both AWS and Azure. To achieve this, you can use Packer to create machine images for both platforms. Once the machine images are created, you can use Terraform to define the infrastructure for each platform. Here's an example of what the Terraform code might look like:

```
provider "aws" {
  region = "us-west-2"
}

resource "aws_instance" "web" {
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "t2.micro"
  count         = 2
}

provider "azurerm" {
  features {}
}

resource "azurerm_resource_group" "rg" {
  name     = "example-rg"
  location = "West US 2"
}

resource "azurerm_virtual_network" "vnet" {
  name                = "example-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" "subnet" {
  name                 = "example-subnet"
  resource_group_name  = azurerm_resource_group.rg.name
  virtual_network_name = azurerm_virtual_network.vnet.name
  address_prefixes     = ["10.0.1.0/24"]
}

resource "azurerm_network_interface" "nic" {
  name                = "example-nic"
  location            = azurerm_resource_group.rg.location
  resource_group_name = azurerm_resource_group.rg.name

ip_configuration {
    name                          = "example-ipconfig"
    subnet_id                     = azurerm_subnet.subnet.id
    private_ip_address_allocation = "Dynamic"
  }
}

resource "azurerm_virtual_machine" "vm" {
  name                  = "example-vm"
  location              = azurerm_resource_group.rg.location
  resource_group_name   = azurerm_resource_group.rg.name
  network_interface_ids = [azurerm_network_interface.nic.id]
  vm_size               = "Standard_DS1_v2"

storage_os_disk {
    name              = "example-osdisk"
    caching           = "ReadWrite"
    create_option     = "FromImage"
    managed_disk_type = "Standard_LRS"
  }

storage_image_reference {
    publisher = "Canonical"
    offer     = "UbuntuServer"
    sku       = "16.04-LTS"
    version   = "latest"
  }

os_profile {
    computer_name  = "example-vm"
    admin_username = "adminuser"
  }

os_profile_linux_config {
    disable_password_authentication = true
  }
}

```

As you can see, this code defines two instances on AWS and one virtual machine on Azure. By using Terraform, you can easily manage the infrastructure for both platforms in a single configuration file.

### Example 2: Multi-Cloud Deployment with Google Cloud and Azure

Now let's imagine that you need to deploy the same web application on Google Cloud and Azure. In this case, you can use Packer to create machine images for both platforms and Terraform to define the infrastructure. Here's an example of what the Terraform code might look like:

```
provider "google" {
  project = "example-project"
  region  = "us-west1"
}

resource "google_compute_instance" "web" {
  name         = "web"
  machine_type = "n1-standard-1"
  zone         = "us-west1-a"
  boot_disk {
    initialize_params {
      image = "debian-cloud/debian-9"
    }
  }
}