This repo contains example Terraform configurations for building AWS infrastructure.
The exercises directory contains 4 different AWS infrastructure provisioning exercises.
Create a simple AWS VPC spanning 2 AZs. Public subnets will be created, together with an internet gateway, and single route table. A t3.micro instance will be deployed and installed with Nginx for web serving. Security groups will be created and deployed to secure all network traffic between the various components.
https://github.com/cloudacademy/terraform-aws/tree/main/exercises/exercise1
├── main.tf
├── outputs.tf
├── terraform.tfvars
└── variables.tf
-
workstation_ip
: The Terraform variableworkstation_ip
represents your workstation's external perimeter public IP address, and needs to be represented using CIDR notation. This IP address is used later on within the Terraform infrastructure provisioning process to lock down SSH access on the instance(s) (provisioned by Terraform) - this is a security safety measure to prevent anyone else from attempting SSH access. The public IP address will be different and unique for each user - the easiest way to get this address is to type "what is my ip address" in a google search. As an example response, lets say Google responded with202.10.23.16
- then the value assigned to the Terraformworkstation_ip
variable would be202.10.23.16/32
(note the/32
is this case indicates that it is a single IP address). -
key_name
: The Terraform variablekey_name
represents the AWS SSH Keypair name that will be used to allow SSH access to the Bastion Host that gets created at provisioning time. If you intend to use the Bastion Host - then you will need to create your own SSH Keypair (typically done within the AWS EC2 console) ahead of time.-
The required Terraform
workstation_ip
andkey_name
variables can be established multiple ways, one of which is to prefix the variable name withTF_VAR_
and have it then set as an environment variable within your shell, something like: -
Linux:
export TF_VAR_workstation_ip=202.10.23.16/32
andexport TF_VAR_key_name=your_ssh_key_name
-
Windows:
set TF_VAR_workstation_ip=202.10.23.16/32
andset TF_VAR_key_name=your_ssh_key_name
-
-
Terraform environment variables are documented here: https://www.terraform.io/cli/config/environment-variables
Create an advanced AWS VPC spanning 2 AZs with both public and private subnets. An internet gateway and NAT gateway will be deployed into it. Public and private route tables will be established. An application load balancer (ALB) will be installed which will load balance traffic across an auto scaling group (ASG) of Nginx web servers. Security groups will be created and deployed to secure all network traffic between the various components.
https://github.com/cloudacademy/terraform-aws/tree/main/exercises/exercise2
├── ec2.userdata
├── main.tf
├── outputs.tf
├── terraform.tfvars
└── variables.tf
-
workstation_ip
: The Terraform variableworkstation_ip
represents your workstation's external perimeter public IP address, and needs to be represented using CIDR notation. This IP address is used later on within the Terraform infrastructure provisioning process to lock down SSH access on the instance(s) (provisioned by Terraform) - this is a security safety measure to prevent anyone else from attempting SSH access. The public IP address will be different and unique for each user - the easiest way to get this address is to type "what is my ip address" in a google search. As an example response, lets say Google responded with202.10.23.16
- then the value assigned to the Terraformworkstation_ip
variable would be202.10.23.16/32
(note the/32
is this case indicates that it is a single IP address). -
key_name
: The Terraform variablekey_name
represents the AWS SSH Keypair name that will be used to allow SSH access to the Bastion Host that gets created at provisioning time. If you intend to use the Bastion Host - then you will need to create your own SSH Keypair (typically done within the AWS EC2 console) ahead of time.-
The required Terraform
workstation_ip
andkey_name
variables can be established multiple ways, one of which is to prefix the variable name withTF_VAR_
and have it then set as an environment variable within your shell, something like: -
Linux:
export TF_VAR_workstation_ip=202.10.23.16/32
andexport TF_VAR_key_name=your_ssh_key_name
-
Windows:
set TF_VAR_workstation_ip=202.10.23.16/32
andset TF_VAR_key_name=your_ssh_key_name
-
-
Terraform environment variables are documented here: https://www.terraform.io/cli/config/environment-variables
Same AWS architecture as used in Exercise 2. This exercise demonstrates a different Terraform technique, using the Terraform "count" meta argument, for configuring the public and private subnets as well as their respective route tables.
https://github.com/cloudacademy/terraform-aws/tree/main/exercises/exercise3
├── ec2.userdata
├── main.tf
├── outputs.tf
├── terraform.tfvars
└── variables.tf
-
workstation_ip
: The Terraform variableworkstation_ip
represents your workstation's external perimeter public IP address, and needs to be represented using CIDR notation. This IP address is used later on within the Terraform infrastructure provisioning process to lock down SSH access on the instance(s) (provisioned by Terraform) - this is a security safety measure to prevent anyone else from attempting SSH access. The public IP address will be different and unique for each user - the easiest way to get this address is to type "what is my ip address" in a google search. As an example response, lets say Google responded with202.10.23.16
- then the value assigned to the Terraformworkstation_ip
variable would be202.10.23.16/32
(note the/32
is this case indicates that it is a single IP address). -
key_name
: The Terraform variablekey_name
represents the AWS SSH Keypair name that will be used to allow SSH access to the Bastion Host that gets created at provisioning time. If you intend to use the Bastion Host - then you will need to create your own SSH Keypair (typically done within the AWS EC2 console) ahead of time.-
The required Terraform
workstation_ip
andkey_name
variables can be established multiple ways, one of which is to prefix the variable name withTF_VAR_
and have it then set as an environment variable within your shell, something like: -
Linux:
export TF_VAR_workstation_ip=202.10.23.16/32
andexport TF_VAR_key_name=your_ssh_key_name
-
Windows:
set TF_VAR_workstation_ip=202.10.23.16/32
andset TF_VAR_key_name=your_ssh_key_name
-
-
Terraform environment variables are documented here: https://www.terraform.io/cli/config/environment-variables
Create an advanced AWS VPC to host a fully functioning cloud native application.
The VPC will span 2 AZs, and have both public and private subnets. An internet gateway and NAT gateway will be deployed into it. Public and private route tables will be established. An application load balancer (ALB) will be installed which will load balance traffic across an auto scaling group (ASG) of Nginx web servers installed with the cloud native application frontend and API. A database instance running MongoDB will be installed in the private zone. Security groups will be created and deployed to secure all network traffic between the various components.
For demonstration purposes only - both the frontend and the API will be deployed to the same set of ASG instances - to reduce running costs.
https://github.com/cloudacademy/terraform-aws/tree/main/exercises/exercise4
The auto scaling web application layer bootstraps itself with both the Frontend and API components by pulling down their latest respective releases from the following repos:
-
Frontend: https://github.com/cloudacademy/voteapp-frontend-react-2020/releases/latest
-
API: https://github.com/cloudacademy/voteapp-api-go/releases/latest
The bootstrapping process for the Frontend and API components is codified within a template_cloudinit_config
block located in the application module's main.tf file:
data "template_cloudinit_config" "config" {
gzip = false
base64_encode = false
#userdata
part {
content_type = "text/x-shellscript"
content = <<-EOF
#! /bin/bash
apt-get -y update
apt-get -y install nginx
apt-get -y install jq
ALB_DNS=${aws_lb.alb1.dns_name}
MONGODB_PRIVATEIP=${var.mongodb_ip}
mkdir -p /tmp/cloudacademy-app
cd /tmp/cloudacademy-app
echo ===========================
echo FRONTEND - download latest release and install...
mkdir -p ./voteapp-frontend-react-2020
pushd ./voteapp-frontend-react-2020
curl -sL https://api.github.com/repos/cloudacademy/voteapp-frontend-react-2020/releases/latest | jq -r '.assets[0].browser_download_url' | xargs curl -OL
INSTALL_FILENAME=$(curl -sL https://api.github.com/repos/cloudacademy/voteapp-frontend-react-2020/releases/latest | jq -r '.assets[0].name')
tar -xvzf $INSTALL_FILENAME
rm -rf /var/www/html
cp -R build /var/www/html
cat > /var/www/html/env-config.js << EOFF
window._env_ = {REACT_APP_APIHOSTPORT: "$ALB_DNS"}
EOFF
popd
echo ===========================
echo API - download latest release, install, and start...
mkdir -p ./voteapp-api-go
pushd ./voteapp-api-go
curl -sL https://api.github.com/repos/cloudacademy/voteapp-api-go/releases/latest | jq -r '.assets[] | select(.name | contains("linux-amd64")) | .browser_download_url' | xargs curl -OL
INSTALL_FILENAME=$(curl -sL https://api.github.com/repos/cloudacademy/voteapp-api-go/releases/latest | jq -r '.assets[] | select(.name | contains("linux-amd64")) | .name')
tar -xvzf $INSTALL_FILENAME
#start the API up...
MONGO_CONN_STR=mongodb://$MONGODB_PRIVATEIP:27017/langdb ./api &
popd
systemctl restart nginx
systemctl status nginx
echo fin v1.00!
EOF
}
}
The ALB will configured with a single listener (port 80). 2 target groups will be established. The frontend target group points to the Nginx web server (port 80). The API target group points to the custom API service (port 8080).
├── main.tf
├── modules
│ ├── application
│ │ ├── main.tf
│ │ ├── outputs.tf
│ │ └── vars.tf
│ ├── bastion
│ │ ├── main.tf
│ │ ├── outputs.tf
│ │ └── vars.tf
│ ├── network
│ │ ├── main.tf
│ │ ├── outputs.tf
│ │ └── vars.tf
│ ├── security
│ │ ├── main.tf
│ │ ├── outputs.tf
│ │ └── vars.tf
│ └── storage
│ ├── install.sh
│ ├── main.tf
│ ├── outputs.tf
│ └── vars.tf
├── outputs.tf
├── terraform.tfvars
└── variables.tf
-
workstation_ip
: The Terraform variableworkstation_ip
represents your workstation's external perimeter public IP address, and needs to be represented using CIDR notation. This IP address is used later on within the Terraform infrastructure provisioning process to lock down SSH access on the instance(s) (provisioned by Terraform) - this is a security safety measure to prevent anyone else from attempting SSH access. The public IP address will be different and unique for each user - the easiest way to get this address is to type "what is my ip address" in a google search. As an example response, lets say Google responded with202.10.23.16
- then the value assigned to the Terraformworkstation_ip
variable would be202.10.23.16/32
(note the/32
is this case indicates that it is a single IP address). -
key_name
: The Terraform variablekey_name
represents the AWS SSH Keypair name that will be used to allow SSH access to the Bastion Host that gets created at provisioning time. If you intend to use the Bastion Host - then you will need to create your own SSH Keypair (typically done within the AWS EC2 console) ahead of time.-
The required Terraform
workstation_ip
andkey_name
variables can be established multiple ways, one of which is to prefix the variable name withTF_VAR_
and have it then set as an environment variable within your shell, something like: -
Linux:
export TF_VAR_workstation_ip=202.10.23.16/32
andexport TF_VAR_key_name=your_ssh_key_name
-
Windows:
set TF_VAR_workstation_ip=202.10.23.16/32
andset TF_VAR_key_name=your_ssh_key_name
-
-
Terraform environment variables are documented here: https://www.terraform.io/cli/config/environment-variables
Refactoring of the Cloud Native Application (excercise 4) to use Ansible for configuration management.
The VPC will span 2 AZs, and have both public and private subnets. An internet gateway and NAT gateway will be deployed into it. Public and private route tables will be established. An application load balancer (ALB) will be installed which will load balance traffic across an auto scaling group (ASG) of Nginx web servers installed with the cloud native application frontend and API. A database instance running MongoDB will be installed in the private zone. Security groups will be created and deployed to secure all network traffic between the various components.
For demonstration purposes only - both the frontend and the API will be deployed to the same set of ASG instances - to reduce running costs.
https://github.com/cloudacademy/terraform-aws/tree/main/exercises/exercise5
The auto scaling web application layer bootstraps itself with both the Frontend and API components by pulling down their latest respective releases from the following repos:
-
Frontend: https://github.com/cloudacademy/voteapp-frontend-react-2020/releases/latest
-
API: https://github.com/cloudacademy/voteapp-api-go/releases/latest
The bootstrapping process for the Frontend and API components is now performed by Ansible. An Ansible playbook is executed from within the root main.tf file:
resource "null_resource" "ansible" {
provisioner "local-exec" {
interpreter = ["/bin/bash", "-c"]
working_dir = "${path.module}/ansible"
command = <<EOT
sleep 120 #time to allow VMs to come online and stabilize
mkdir -p ./logs
sed \
-e 's/BASTION_IP/${module.bastion.public_ip}/g' \
-e 's/WEB_IPS/${join("\\n", module.application.private_ips)}/g' \
-e 's/MONGO_IP/${module.storage.private_ip}/g' \
./templates/hosts > hosts
sed \
-e 's/BASTION_IP/${module.bastion.public_ip}/g' \
-e 's/SSH_KEY_NAME/${var.key_name}/g' \
./templates/ssh_config > ssh_config
#required for macos only
export OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES
#ANSIBLE
ansible-playbook -v \
-i hosts \
--extra-vars "ALB_DNS=${module.application.dns_name}" \
--extra-vars "MONGODB_PRIVATEIP=${module.storage.private_ip}" \
./playbooks/master.yml
echo finished!
EOT
}
depends_on = [
module.bastion,
module.application
]
}
The ALB will configured with a single listener (port 80). 2 target groups will be established. The frontend target group points to the Nginx web server (port 80). The API target group points to the custom API service (port 8080).
├── main.tf
├── ansible
│ ├── ansible.cfg
│ ├── logs
│ │ └── ansible.log
│ ├── playbooks
│ │ ├── database.yml
│ │ ├── deployapp.yml
│ │ ├── files
│ │ │ ├── api.sh
│ │ │ ├── db.sh
│ │ │ └── frontend.sh
│ │ └── master.yml
│ └── templates
│ ├── hosts
│ └── ssh_config
├── modules
│ ├── application
│ │ ├── main.tf
│ │ ├── outputs.tf
│ │ └── vars.tf
│ ├── bastion
│ │ ├── main.tf
│ │ ├── outputs.tf
│ │ └── vars.tf
│ ├── network
│ │ ├── main.tf
│ │ ├── outputs.tf
│ │ └── vars.tf
│ ├── security
│ │ ├── main.tf
│ │ ├── outputs.tf
│ │ └── vars.tf
│ └── storage
│ ├── install.sh
│ ├── main.tf
│ ├── outputs.tf
│ └── vars.tf
├── outputs.tf
├── terraform.tfvars
└── variables.tf
-
workstation_ip
: The Terraform variableworkstation_ip
represents your workstation's external perimeter public IP address, and needs to be represented using CIDR notation. This IP address is used later on within the Terraform infrastructure provisioning process to lock down SSH access on the instance(s) (provisioned by Terraform) - this is a security safety measure to prevent anyone else from attempting SSH access. The public IP address will be different and unique for each user - the easiest way to get this address is to type "what is my ip address" in a google search. As an example response, lets say Google responded with202.10.23.16
- then the value assigned to the Terraformworkstation_ip
variable would be202.10.23.16/32
(note the/32
is this case indicates that it is a single IP address). -
key_name
: The Terraform variablekey_name
represents the AWS SSH Keypair name that will be used to allow SSH access to the Bastion Host that gets created at provisioning time. If you intend to use the Bastion Host - then you will need to create your own SSH Keypair (typically done within the AWS EC2 console) ahead of time.-
The required Terraform
workstation_ip
andkey_name
variables can be established multiple ways, one of which is to prefix the variable name withTF_VAR_
and have it then set as an environment variable within your shell, something like: -
Linux:
export TF_VAR_workstation_ip=202.10.23.16/32
andexport TF_VAR_key_name=your_ssh_key_name
-
Windows:
set TF_VAR_workstation_ip=202.10.23.16/32
andset TF_VAR_key_name=your_ssh_key_name
-
-
Terraform environment variables are documented here: https://www.terraform.io/cli/config/environment-variables
Launch an EKS cluster and deploy a pre-built cloud native web app.
The following EKS architecture will be provisioned using Terraform:
The cloud native web app that gets deployed is based on the following codebase:
The following public AWS modules are used to launch the EKS cluster:
Additionally, the following providers are utilised:
The EKS cluster will be provisioned with 2 worker nodes based on m5.large spot instances. This configuration is suitable for the demonstration purposes of this exercise. Production environments are likely more suited to on-demand always on instances.
The cloud native web app deployed is configured within the ./k8s
directory, and is installed automatically using the following null resource configuration:
resource "null_resource" "deploy_app" {
triggers = {
always_run = "${timestamp()}"
}
provisioner "local-exec" {
interpreter = ["/bin/bash", "-c"]
working_dir = path.module
command = <<EOT
echo deploying app...
./k8s/app.install.sh
EOT
}
depends_on = [
helm_release.nginx_ingress
]
}
The Helm provider is used to automatically install the Nginx Ingress Controller at provisioning time:
provider "helm" {
kubernetes {
host = module.eks.cluster_endpoint
cluster_ca_certificate = base64decode(module.eks.cluster_certificate_authority_data)
exec {
api_version = "client.authentication.k8s.io/v1beta1"
command = "aws"
args = ["eks", "get-token", "--cluster-name", module.eks.cluster_name]
}
}
}
resource "helm_release" "nginx_ingress" {
name = "nginx-ingress"
repository = "https://helm.nginx.com/stable"
chart = "nginx-ingress"
namespace = "nginx-ingress"
create_namespace = true
set {
name = "service.type"
value = "ClusterIP"
}
set {
name = "controller.service.name"
value = "nginx-ingress-controller"
}
}
Deploy a set of serverless apps using API Gateway and Lambda Functions.
The following EKS architecture will be provisioned using Terraform:
The cloud native web app that gets deployed is based on the following codebase:
The following public AWS modules are used to launch the EKS cluster:
Additionally, the following providers are utilised:
The EKS cluster will be provisioned with 2 worker nodes based on m5.large spot instances. This configuration is suitable for the demonstration purposes of this exercise. Production environments are likely more suited to on-demand always on instances.
The cloud native web app deployed is configured within the ./k8s
directory, and is installed automatically using the following null resource configuration:
resource "null_resource" "deploy_app" {
triggers = {
always_run = "${timestamp()}"
}
provisioner "local-exec" {
interpreter = ["/bin/bash", "-c"]
working_dir = path.module
command = <<EOT
echo deploying app...
./k8s/app.install.sh
EOT
}
depends_on = [
helm_release.nginx_ingress
]
}
The Helm provider is used to automatically install the Nginx Ingress Controller at provisioning time:
provider "helm" {
kubernetes {
host = module.eks.cluster_endpoint
cluster_ca_certificate = base64decode(module.eks.cluster_certificate_authority_data)
exec {
api_version = "client.authentication.k8s.io/v1beta1"
command = "aws"
args = ["eks", "get-token", "--cluster-name", module.eks.cluster_name]
}
}
}
resource "helm_release" "nginx_ingress" {
name = "nginx-ingress"
repository = "https://helm.nginx.com/stable"
chart = "nginx-ingress"
namespace = "nginx-ingress"
create_namespace = true
set {
name = "service.type"
value = "ClusterIP"
}
set {
name = "controller.service.name"
value = "nginx-ingress-controller"
}
}