Table of contents
Immutable infrastructure is an approach to managing services and software deployments on IT resources wherein components are replaced rather than changed. An application or services is effectively redeployed each time any change occurs.
In this post I am going to show how one can create a workflow based in the idea of immutable infrastructure. You can find the full working code in github https://github.com/apotitech/immutable-cluster.git.
The Recipe
Since the goal is to simply replace the instance on each application release, we want to create a machine image containing the application. This way we can swap out the whole instance quickly without further installation steps after provisioning. This is sometimes called a golden image. We are going to use Packer & Ansible for this.
Further, we want to manage our infrastructure as code. Terraform is a good choice for this. It can create, change and destroy infrastructure remotely and keeps track of the current state of our system.
With a golden image and infrastructure as code, we can throw away the complete environment, in this case the vpc with instances, and create a new one within minutes if we wish. Usually we only want to swap the instances though.
Prerequisites
To follow along you need:
an AWS account & access tokens
have Ansible installed
have Packer installed
have Terraform installed
have the AWS CLI version 2 installed
Creating a Custom Image with Packer
If you are using a custom vpc, make sure to configure Packer to use a subnet with automatic public ip assignment and a route to the internet gateway.
Packer File
First we create a Packer file with some information about the image we want to create.
Most importantly We specify the region. By default our AMI will only be available in this region.
We specify Ansible as provisioner. It will execute the playbook on the temporary instance to apply additional configuration.
variable "aws_access_key" {
sensitive = true
}
variable "aws_secret_key" {
sensitive = true
}
source "amazon-ebs" "example" {
access_key = var.aws_access_key
secret_key = var.aws_secret_key
ssh_timeout = "30s"
region = "eu-central-1"
// amazon linux 2
source_ami = "ami-0db9040eb3ab74509"
ssh_username = "ec2-user"
ami_name = "packer nginx"
instance_type = "t2.micro"
skip_create_ami = false
}
build {
sources = [
"source.amazon-ebs.example"
]
provisioner "ansible" {
playbook_file = "playbook.yml"
}
}
Ansible Playbook
Once Packer has created the temporary instance, we use Ansible to apply additional configuration.
The playbook tells ansible to install and enable the nginx service. The result will be nginx serving the default page on port 80 when the instance is booted.
---
- name: set up nginx
hosts: default
become: true
tasks:
- name: ensure extra repo is available
yum:
name: [amazon-linux-extras]
state: present
- name: enable nginx repo
shell: amazon-linux-extras enable nginx1
- name: yum-clean-metadata
command: yum clean metadata
args:
warn: no
- name: install nginx
yum:
name: [nginx]
state: latest
- name: enable nginx service
service:
name: nginx
enabled: true
Build
With the 2 configuration files we can validate the input and build our custom AMI in AWS.
packer validate .
packer build .
The AMI
Once the process is completed, we can use the AWS CLI to inspect the created AMI and find the ImageId.
$ aws ec2 describe-images --owner self --region eu-central-1
{
"Images": [
{
"Architecture": "x86_64",
"CreationDate": "2021-04-18T00:00:05.000Z",
"ImageId": "ami-01cce7ac6df33f08e",
"ImageLocation": "<your_account_id>/packer nginx",
"ImageType": "machine",
"Public": false,
"OwnerId": "<your_account_id>",
"PlatformDetails": "Linux/UNIX",
"UsageOperation": "RunInstances",
"State": "available",
"BlockDeviceMappings": [
{
"DeviceName": "/dev/xvda",
"Ebs": {
"DeleteOnTermination": true,
"SnapshotId": "snap-0692717e44e63cbd1",
"VolumeSize": 8,
"VolumeType": "gp2",
"Encrypted": false
}
}
],
"EnaSupport": true,
"Hypervisor": "xen",
"Name": "packer nginx",
"RootDeviceName": "/dev/xvda",
"RootDeviceType": "ebs",
"SriovNetSupport": "simple",
"VirtualizationType": "hvm"
}
]
}
Deploying the Infrastructure with Terraform
Now we have our custom AMI in the eu-central-1 region. Next we will use Terraform to deploy this image together with the required infrastructure.
variable "aws_access_key" {
sensitive = true
}
variable "aws_secret_key" {
sensitive = true
}
variable "ami_id" {
default = ""
}
variable "domain" {
default = ""
}
terraform {
required_providers {
aws = {
source = "hashicorp/aws"
version = "~> 3.0"
}
}
}
provider "aws" {
region = "eu-central-1"
access_key = var.aws_access_key
secret_key = var.aws_secret_key
}
VPC
First we create a simple VPC with 2 subnets in different availability zones.
resource "aws_vpc" "packer" {
cidr_block = "10.0.0.0/16"
tags = {
Name = "packer"
Description = "sample vpc with 2 public subnets in 2 availability zones and a network load balancer for high availability"
}
}
resource "aws_internet_gateway" "inet" {
vpc_id = aws_vpc.packer.id
tags = {
Name = "packer internet gateway"
}
}
resource "aws_default_route_table" "public" {
default_route_table_id = aws_vpc.packer.default_route_table_id
route {
cidr_block = "0.0.0.0/0"
gateway_id = aws_internet_gateway.inet.id
}
tags = {
Name = "public route table"
}
}
resource "aws_subnet" "a" {
vpc_id = aws_vpc.packer.id
cidr_block = "10.0.0.0/24"
availability_zone = "eu-central-1a"
tags = {
Name = "public subnet a"
}
map_public_ip_on_launch = true
}
resource "aws_subnet" "b" {
vpc_id = aws_vpc.packer.id
cidr_block = "10.0.1.0/24"
availability_zone = "eu-central-1b"
tags = {
Name = "public subnet b"
}
map_public_ip_on_launch = true
}
Security Groups
Next, we create the security groups.
The default security group has only a reference to itself. It is used to allow traffic to flow between the ALB and its targets.
The second security group is to allow tcp traffic from the public web to the ALB on port 80(HTTP) and 443 (HTTPS).
resource "aws_default_security_group" "internal" {
vpc_id = aws_vpc.packer.id
tags = {
Name = "default internal sg"
}
ingress {
protocol = -1
self = true
from_port = 0
to_port = 0
description = "self ref"
}
egress {
protocol = -1
self = true
from_port = 0
to_port = 0
description = "self ref"
}
}
resource "aws_security_group" "web" {
vpc_id = aws_vpc.packer.id
tags = {
Name = "web sg for nginx"
}
ingress {
description = "http traffic"
from_port = 80
to_port = 80
protocol = "tcp"
cidr_blocks = ["0.0.0.0/0"]
ipv6_cidr_blocks = ["::/0"]
}
ingress {
description = "http traffic"
from_port = 443
to_port = 443
protocol = "tcp"
cidr_blocks = ["0.0.0.0/0"]
ipv6_cidr_blocks = ["::/0"]
}
egress {
from_port = 0
to_port = 0
protocol = "-1"
cidr_blocks = ["0.0.0.0/0"]
ipv6_cidr_blocks = ["::/0"]
}
}
Logging
We are going to create an S3 bucket with the required access policy to use it as log destination for the ALB in the next section.
resource "aws_s3_bucket" "logs" {
bucket = "com.myorg.logs"
acl = "private"
force_destroy = true
tags = {
Name = "nginx cluster access logs"
Environment = "Dev"
}
}
data "aws_elb_service_account" "main" {
region = "eu-central-1"
}
resource "aws_s3_bucket_policy" "logs" {
bucket = aws_s3_bucket.logs.id
policy = <<POLICY
{
"Version": "2012-10-17",
"Id": "allow-elb-logs",
"Statement": [
{
"Sid": "RegionRootArn",
"Effect": "Allow",
"Principal": {
"AWS": "${data.aws_elb_service_account.main.arn}"
},
"Action": "s3:PutObject",
"Resource": "${aws_s3_bucket.logs.arn}/*"
},
{
"Sid": "AWSLogDeliveryWrite",
"Effect": "Allow",
"Principal": {
"Service": "delivery.logs.amazonaws.com"
},
"Action": "s3:PutObject",
"Resource": "${aws_s3_bucket.logs.arn}/*",
"Condition": {
"StringEquals": {
"s3:x-amz-acl": "bucket-owner-full-control"
}
}
},
{
"Sid": "AWSLogDeliveryAclCheck",
"Effect": "Allow",
"Principal": {
"Service": "delivery.logs.amazonaws.com"
},
"Action": "s3:GetBucketAcl",
"Resource": "${aws_s3_bucket.logs.arn}"
}
]
}
POLICY
}
Load balancing
Next, an application load balancer (ALB) is created with a 2 listeners.
The first listener will listen on port 80 and redirect the traffic to port 443.
The second listener will serve a tls certificate, that is imported from ACM, on port 443. After the TLS handshake it will forward the traffic over http on port 80 to the target group, also known asl TLS Termination.
I am assuming that you have already uploaded your own cert or that you have issued one with ACM. There a branch without tls in this repo.
The target group will be populated by the auto scaling group in the next section.
resource "aws_lb" "web" {
name = "packer-nginx"
internal = false
load_balancer_type = "application"
security_groups = [
aws_default_security_group.internal.id,
aws_security_group.web.id,
]
subnets = [
aws_subnet.a.id,
aws_subnet.b.id
]
access_logs {
bucket = aws_s3_bucket.logs.id
enabled = true
}
}
resource "aws_lb_target_group" "web" {
name = "web-tg"
port = 80
protocol = "HTTP"
vpc_id = aws_vpc.packer.id
}
resource "aws_lb_listener" "web" {
load_balancer_arn = aws_lb.web.arn
port = "80"
protocol = "HTTP"
default_action {
type = "redirect"
redirect {
port = "443"
protocol = "HTTPS"
status_code = "HTTP_301"
}
}
}
data "aws_acm_certificate" "mycert" {
domain = var.domain
statuses = ["ISSUED"]
most_recent = true
}
resource "aws_lb_listener" "websecure" {
load_balancer_arn = aws_lb.web.arn
port = "443"
protocol = "HTTPS"
ssl_policy = "ELBSecurityPolicy-2016-08"
certificate_arn = data.aws_acm_certificate.mycert.arn
default_action {
type = "forward"
target_group_arn = aws_lb_target_group.web.arn
}
}
Autoscaling
Lastly, we create a launch template and auto scaling group to launch new instances of the custom AMI.
We will require a minimum of 2 instances with a desired count of 2 instances. Optionally we allow to scale up to 4 instances if instances reach their resource limit.
The strategy of the placement group is set to partition which means that the instances should get spread across the racks in the physical data centers.
resource "aws_placement_group" "web" {
name = "web-pl"
strategy = "partition"
}
resource "aws_launch_template" "web" {
name_prefix = "web-lt-"
image_id = var.ami_id
instance_type = "t2.micro"
vpc_security_group_ids = [
aws_default_security_group.internal.id,
]
}
resource "aws_autoscaling_group" "web" {
name = "webscale"
vpc_zone_identifier = [aws_subnet.a.id, aws_subnet.b.id]
desired_capacity = 2
max_size = 4
min_size = 2
placement_group = aws_placement_group.web.id
launch_template {
id = aws_launch_template.web.id
version = "$Latest"
}
lifecycle {
ignore_changes = [load_balancers, target_group_arns]
}
}
resource "aws_autoscaling_attachment" "web" {
autoscaling_group_name = aws_autoscaling_group.web.id
alb_target_group_arn = aws_lb_target_group.web.arn
}
Deploy
Now we can deploy the infrastructure. Run terraform apply and confirm the prompt. The process will take a couple minutes until all the resources are created and ready.
terraform apply
You can use AWS CLI to see if the targets of the load balancer are healthy.
They may not be ready yet. If that is the case, just wait a couple minutes and check again.
Once the targets are marked as healthy, we need to point a CNAME record from our domain to the ELB DNS. I am managing my certificate with Linode, so I will give an example of how to do it via linode-cli.
You can now visit the url in your browse under the configured subdomain.
Thats it!
The application is deployed from a custom AMI across 2 availability zones and utilizing autoscaling. The traffic is routed via ELB which also performs TLS Termination.
Additionally, we have our whole infrastructure as code which we can source control.
Cleaning Up
In order to avoid cost, lets remove all created resources.
terraform destroy
Since the AMI and snapshot was not created with Terraform, it wont be destroyed by the former command. We are going to remove them via CLI.
Deregister Image
aws ec2 deregister-image --image-id <your-ami-id>
Find the snapshot Id
aws ec2 describe-snapshots --owner self
Delete snapshot
aws ec2 delete-snapshot --snapshot-id <your-snap-id>
Remove cname record
linode-cli domains records-delete <main-id> <record-id>
Conclusion
In this secondary tutorial, we used Packer, Terraform and Ansible to build a Pipeline and deploy our application to AWS.
#YouAreAwesome #StayAwesome
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