EC2 Auto Scaling with Ansible

We use Ansible to manage application deployments to EC2 with Auto Scaling. It's particularly suited because it lends itself to easy integration with existing processes such as CI, enabling rapid development of a continuous deployment pipeline. One crucial feature is that it is able to hand-hold a rolling deploy (that is, zero downtime) by terminating and replacing instances in batches. Typically when we deploy to EC2, we do so in an automated fashion which makes it important to have rollback capability and for this, we typically maintain a short history of Amazon Machine Images (AMIs) and Launch Configurations which are associated with a particular Auto Scaling Group (ASG). In the event you wish to roll back to a particular version of your application, you can simply associate your ASG with the previously known working launch configuration and replace all your instances.

Our normal workflow for auto scaling deployments starts with an Ansible playbook which runs through the deploy lifecycle. Each step along the way is represented by a role and applied in order, keeping the main playbook lean and configurable. Depending on our client's requirements, that playbook might be triggered in a number of ways such as the final step in a continuous integration build, or on demand via Hubot in a Slack/Flowdock/IRC chat.

In this post we'll walk through each stage of the build and deployment process, and use Ansible to perform all the work. The goal is to build our entire environment from scratch, save for a few manually created resources at the outset.

Preparing AWS

We'll be using EC2 Classic for these examples, although they can be trivially adapted for VPC. Start by creating an EC2 Security Group for your application, taking care to open the necessary ports for your application in addition to TCP/22 for SSH.

Add a new keypair for SSH access to your instances. You can either create a new private/public keypair or upload your existing SSH public key.

You may optionally register and host a domain name with AWS Route 53. If you do so, the domain will be pointed at your application so that you don't have to browse to it by using an automatically assigned AWS hostname.

Setting up Ansible

Ansible uses Boto for AWS interactions, so you'll need that installed on your control host. We're also going to make some use of the AWS CLI tools, so get those too. Your platform may differ, but the following will work for most platforms:

pip install python-boto awscli

We also assume Ansible 1.9.x, for Ubuntu you can get that from the Ansible PPA.

add-apt-repository ppa:ansible/ansible
apt-get install ansible

You should place your AWS access/secret keys into

~/.aws/credentials

[Credentials]
aws_access_key_id = 
aws_secret_access_key = 

We'll be using the ec2.py dynamic inventory script for Ansible so we can address our EC2 instances by various attributes instead of hard coding hostnames into an inventory file. It's not included with the Ubuntu distribution(s) of Ansible, so we'll grab it from GitHub. Place ec2.py and ec2.ini into

/etc/ansible/inventory

Modify

/etc/ansible/ansible.cfg

# /etc/ansible/ansible.cfg
inventory = /etc/ansible/inventory

Step 1: Launch a new EC2 instance

A prerequisite to setting up an application for auto scaling involves building an AMI containing your working application, which will be used to launch new instances to meet demand. We'll start by launching a new instance onto which we can deploy our application. Create the following files:

---
# group_vars/all.yml

region: us-east-1
zone: us-east-1a
keypair: YOUR_KEYPAIR
security_groups: YOUR_SECURITY_GROUP
instance_type: m3.medium
volumes:

device_name: /dev/sda1
device_type: gp2
volume_size: 20
delete_on_termination: true

---

deploy.yml

hosts: localhost
connection: local
gather_facts: no
roles:

role: launch
name: ami-build

---
roles/launch/tasks/main.yml



name: Search for the latest Ubuntu 14.04 AMI
ec2_ami_find:
  region: "{{ region }}"
  name: "ubuntu/images/hvm-ssd/ubuntu-trusty-14.04-amd64-server-*"
  owner: 099720109477
  sort: name
  sort_order: descending
  sort_end: 1
  no_result_action: fail
register: ami_result

name: Launch new instance
ec2:
  region: "{{ region }}"
  keypair: "{{ keypair }}"
  zone: "{{ zone }}"
  group: "{{ security_groups }}"
  image: "{{ ami_result.results[0].ami_id }}"
  instance_type: "{{ instance_type }}"
  instance_tags:
Name: "{{ name }}"
  volumes: "{{ volumes }}"
  wait: yes
register: ec2

name: Add new instances to host group
add_host:
  name: "{{ item.public_dns_name }}"
  groups: "{{ name }}"
  ec2_id: "{{ item.id }}"
with_items: ec2.instances

name: Wait for instance to boot
wait_for:
  host: "{{ item.public_dns_name }}"
  port: 22
  delay: 30
  timeout: 300
  state: started
with_items: ec2.instances

The ec2amifind module is a new addition to Ansible 2.0 but has not been backported to 1.9, so we'll need to import this module from GitHub and place it into the

library/

deploy.yml

Run the playbook with

ansible-playbook deploy.yml -vv

Step 2: Deploy the application

Now we'll use Ansible to deploy our application and start it. We'll deploy a sample Node.js web application, the source code of which is kept in a public git repository. Ansible is going to clone and checkout our application at a desired revision on the target instance and configure it to start on boot, in addition to setting up a web server.

---
# deploy.yml


hosts: localhost
connection: local
gather_facts: no
roles:

role: launch
name: ami-build


hosts: ami-build
roles:

deploy
nginx

---
roles/deploy/tasks/main.yml



name: Install git
apt:
  pkg: git
  state: present
sudo: yes

name: Create www directory
file:
  path: /srv/www
  owner: ubuntu
  group: ubuntu
  state: directory
sudo: yes

name: Clone repository
git:
  repo: "https://github.com/atplanet/hello-world-express-app.git"
  dest: /srv/www/webapp
  version: master

name: Install upstart script
copy:
  src: upstart.conf
  dest: /etc/upstart/webapp.conf
sudo: yes

name: Enable and start the application
service:
  name: webapp
  enabled: yes
  state: restarted
sudo: yes

# roles/deploy/files/upstart.conf



description "Sample Node.js app"
author "Tom Bamford"
start on (local-filesystems and net-device-up)
stop on runlevel [06]
env IP="127.0.0.1"
env NODE_ENV="production"
setuid ubuntu
respawn
exec node /srv/www/webapp/app.js

---

roles/nginx/tasks/main.yml

name: Install Nginx
apt:
  pkg: nginx
  state: present
sudo: yes

name: Configure Nginx
copy:
  src: nginx.conf
  dest: /etc/sites-enabled/default
sudo: yes

name: Enable and start Nginx
service:
  name: nginx
  enabled: yes
  state: restarted
sudo: yes

# roles/nginx/files/nginx.conf



server {
  listen 80 default_server;
  location / {
    proxy_pass http://127.0.0.1:8000;
  }
}

Running the playbook again will launch another instance, install some useful packages, deploy our application and set up Nginx as our web server. If you browse to the newest instance at its hostname, as reported in the output of ansible-playbook, you should see a "Hello World" page.

Step 3: Build the AMI

Now that the application is deployed and running, we can use the newly launched instance to build an AMI. Create the

build-ami

---
# deploy.yml


hosts: localhost
connection: local
gather_facts: no
roles:

role: launch
name: ami-build


hosts: ami-build
roles:

deploy
nginx


hosts: localhost
connection: local
gather_facts: no
roles:

create-ami

---
roles/build-ami/tasks/main.yml



name: Create AMI
ec2_ami:
  region: "{{ region }}"
  instance_id: "{{ ec2_id }}"
  name: "webapp-{{ ansible_date_time.iso8601 | regex_replace('[^a-zA-Z0-9]', '-') }}"
  wait: yes
  state: present
register: ami

Step 4: Terminate old instances

You'll probably have noticed by now that each time the playbook is run, Ansible launches a new instance. At this rate, we'll keep accumulating instances that we don't need, so we will add another role and a new task to locate these instances and terminate them. Now, after Ansible successfully launches a new instance, it will terminate any existing instances immediately afterwards.

---
# deploy.yml


name: Find existing instance(s)
hosts: "tag_Name_ami-build"
gather_facts: false
tags: find
tasks:

name: Add to old-ami-build group
group_by:
  key: old-ami-build


hosts: localhost
connection: local
gather_facts: no
roles:

role: launch
name: ami-build


hosts: ami-build
roles:

deploy
nginx


hosts: localhost
connection: local
gather_facts: no
roles:

create-ami


hosts: old-ami-build
roles:

terminate

---
roles/terminate/tasks/main.yml



name: Terminate old instance(s)
ec2:
  instance_ids: "{{ ec2_id }}"
  region: "{{ region }}"
  state: absent
  wait: yes

Step 5: Create a Launch Configuration

Our AMI is built, so now we'll want to create a new Launch Configuration to describe the new instances that should be launched from this AMI. We'll create another role to handle that.

---
# deploy.yml


name: Find existing instance(s)
hosts: "tag_Name_ami-build"
gather_facts: false
tags: find
tasks:

name: Add to old-ami-build group
group_by:
  key: old-ami-build


hosts: localhost
connection: local
gather_facts: no
roles:

role: launch
name: ami-build


hosts: ami-build
roles:

deploy
nginx


hosts: localhost
connection: local
gather_facts: no
roles:

create-ami
create-launch-configuration


hosts: old-ami-build
roles:

terminate

---
roles/create-launch-configuration/tasks/main.yml



name: Create Launch Configuration
ec2_lc:
  region: "{{ region }}"
  name: "webapp-{{ ansible_date_time.iso8601 | regex_replace('[^a-zA-Z0-9]', '-') }}"
  image_id: "{{ ami.image_id }}"
  key_name: "{{ keypair }}"
  instance_type: "{{ instance_type }}"
  security_groups: "{{ security_groups }}"
  volumes: "{{ volumes }}"
  instance_monitoring: yes

Step 6: Create an Elastic Load Balancer

Clients will connect to an Elastic Load Balancer which will distribute incoming requests among the instances we have launched into our upcoming Auto Scaling Group. Again we'll create another role to handle the management of the ELB, and apply it from our playbook.

---
# deploy.yml


name: Find existing instance(s)
hosts: "tag_Name_ami-build"
gather_facts: false
tags: find
tasks:

name: Add to old-ami-build group
group_by:
  key: old-ami-build


hosts: localhost
connection: local
gather_facts: no
roles:

role: launch
name: ami-build


hosts: ami-build
roles:

deploy
nginx


hosts: localhost
connection: local
gather_facts: no
roles:

create-ami
create-launch-configuration
load-balancer


hosts: old-ami-build
roles:

terminate

---
roles/load-balancer/tasks/main.yml



name: Configure Elastic Load Balancers
ec2_elb_lb:
  region: "{{ region }}"
  name: webapp
  state: present
  zones: "{{ zone }}"
  connection_draining_timeout: 60
  listeners:
- protocol: http
  load_balancer_port: 80
  instance_port: 80
  health_check:
ping_protocol: http
ping_port: 80
ping_path: "/"
response_timeout: 10
interval: 30
unhealthy_threshold: 6
healthy_threshold: 2
register: elb_result

Step 7: Create and configure an Auto Scaling Group

We'll create an Auto Scaling Group and configure it to use the Launch Configuration we previously created. Within the boundaries that we define, AWS will launch instances into the ASG dynamically based on the current load across all instances. Equally when the load drops, some instances will be terminated accordingly. Exactly how many instances are launched or terminated is defined in one or more scaling policies, which are also created and linked to the ASG.

---
# deploy.yml


name: Find existing instance(s)
hosts: "tag_Name_ami-build"
gather_facts: false
tags: find
tasks:

name: Add to old-ami-build group
group_by:
  key: old-ami-build


hosts: localhost
connection: local
gather_facts: no
roles:

role: launch
name: ami-build


hosts: ami-build
roles:

deploy
nginx


hosts: localhost
connection: local
gather_facts: no
roles:

create-ami
create-launch-configuration
load-balancer
auto-scaling


hosts: old-ami-build
roles:

terminate

---
roles/auto-scaling/tasks/main.yml



name: Retrieve current Auto Scaling Group properties
command: "aws --region {{ region }} autoscaling describe-auto-scaling-groups --auto-scaling-group-names webapp"
register: asg_properties_result

name: Set asg_properties variable from JSON output if the Auto Scaling Group already exists
set_fact:
  asg_properties: "{{ (asg_properties_result.stdout | from_json).AutoScalingGroups[0] }}"
when: (asg_properties_result.stdout | from_json).AutoScalingGroups | count

name: Configure Auto Scaling Group and perform rolling deploy
ec2_asg:
  region: "{{ region }}"
  name: webapp
  launch_config_name: webapp
  availability_zones: "{{ zone }}"
  health_check_type: ELB
  health_check_period: 300
  desired_capacity: "{{ asg_properties.DesiredCapacity | default(2) }}"
  replace_all_instances: yes
  replace_batch_size: "{{ (asg_properties.DesiredCapacity | default(2) / 4) | round(0, 'ceil') | int }}"
  min_size: 2
  max_size: 10
  load_balancers:
- webapp
  state: present
register: asg_result

name: Configure Scaling Policies
ec2_scaling_policy:
  region: "{{ region }}"
  name: "{{ item.name }}"
  asg_name: webapp
  state: present
  adjustment_type: "{{ item.adjustment_type }}"
  min_adjustment_step: "{{ item.min_adjustment_step }}"
  scaling_adjustment: "{{ item.scaling_adjustment }}"
  cooldown: "{{ item.cooldown }}"
with_items:

name: "Increase Group Size"
adjustment_type: "ChangeInCapacity"
scaling_adjustment: +1
min_adjustment_step: 1
cooldown: 180
name: "Decrease Group Size"
adjustment_type: "ChangeInCapacity"
scaling_adjustment: -1
min_adjustment_step: 1
cooldown: 300
register: sp_result


name: Determine Metric Alarm configuration
set_fact:
  metric_alarms:
- name: "{{ asg_name }}-ScaleUp"
  comparison: ">="
  threshold: 50.0
  alarm_actions:
    - "{{ sp_result.results[0].arn }}"
- name: "{{ asg_name }}-ScaleDown"
  comparison: "<="
  threshold: 20.0
  alarm_actions:
    - "{{ sp_result.results[1].arn }}"

name: Configure Metric Alarms and link to Scaling Policies
ec2_metric_alarm:
  region: "{{ region }}"
  name: "{{ item.name }}"
  state: present
  metric: "CPUUtilization"
  namespace: "AWS/EC2"
  statistic: "Average"
  comparison: "{{ item.comparison }}"
  threshold: "{{ item.threshold }}"
  period: 60
  evaluation_periods: 5
  unit: "Percent"
  dimensions:
AutoScalingGroupName: "{{ asg_name }}"
  alarm_actions: "{{ item.alarm_actions }}"
with_items: metric_alarms
when: max_size > 1
register: ma_result

There's more going on here too. We not only configure our ASG and scaling policies, but also create CloudWatch metric alarms to measure the load across our instances, and associate them with the corresponding scaling policies to complete our configuration.

Here we have configured our CloudWatch alarms to trigger based on aggregate CPU usage within our auto scaling group. When the average CPU utilization exceeds 50% across your instances for 5 consecutive samples taken every 60 seconds (i.e. 5 minutes), a scaling event will be triggered that launches a new instance to relieve the load. A corresponding CloudWatch alarm also triggers a scaling event to terminate an instance from the auto scaling group when the average CPU utilization drops below 20% across your instances for the same sample period.

The minimum and maximum sizes for the auto scaling group are set to 2 and 10 respectively. It's important to get these values right for your application workload. You do not want to be under resourced for early peaks in traffic, and for redundancy reasons it's a good idea to always have at least 2 instances in service. Equally you probably want your application to scale for peak periods, but perhaps not beyond a safety limit in the event you receive massive amounts of traffic which could result in escalating costs.

Particularly important to note here is how we configure the

ec2_asg

desired_capacity

replace_batch_size

replace_all_instances

replace_batch_size

Step 8: Update DNS (optional)

If you have a domain name, or subdomain, set up with AWS Route 53, you can have Ansible update the DNS records to point to your Auto Scaling Group.

---
# deploy.yml


name: Find existing instance(s)
hosts: "tag_Name_ami-build"
gather_facts: false
tags: find
tasks:

name: Add to old-ami-build group
group_by:
  key: old-ami-build


hosts: localhost
connection: local
gather_facts: no
roles:

role: launch
name: ami-build


hosts: ami-build
roles:

deploy
nginx


hosts: localhost
connection: local
gather_facts: no
roles:

create-ami
create-launch-configuration
load-balancer
auto-scaling
dns


hosts: old-ami-build
roles:

terminate

---
roles/dns/tasks/main.yml



name: Update DNS
route53:
  command: create
  overwrite: yes
  zone: "{{ domain }}"
  record: "www.{{ domain }}"
  type: CNAME
  ttl: 300
  value: "{{ elb_result.elb.dns_name }}"

Step 9: Cleaning up

Whilst we already configured Ansible to terminate old instances used for building AMIs, right now we will start to accumulate launch configurations and AMIs each time we invoke the

deploy.yml

Note that whilst you can request increased limits per region for your account, in our experience sometimes these requests are refused on the grounds that AWS would prefer for you to clean up your cruft instead of relying on perpetual service limit increases.

Leaving unused resources lying around is not very good practise in any case, and we certainly don't want to be paying for those resources unnecessarily. To fix this, we'll make use of the

ec2_ami_find

ec2_ami

---
# deploy.yml


name: Find existing instance(s)
hosts: "tag_Name_ami-build"
gather_facts: false
tags: find
tasks:

name: Add to old-ami-build group
group_by:
  key: old-ami-build


hosts: localhost
connection: local
gather_facts: no
roles:

role: launch
name: ami-build


hosts: ami-build
roles:

deploy
nginx


hosts: ami-build
connection: local
gather_facts: no
roles:

create-ami
create-launch-configuration
load-balancer
auto-scaling
dns


hosts: localhost
connection: local
gather_facts: no
roles:

delete-old-launch-configurations
delete-old-amis


hosts: old-ami-build
connection: local
gather_facts: no
roles:

terminate

---
roles/delete-old-amis/tasks/main.yml



ec2_ami_find:
  region: "{{ region }}"
  owner: self
  name: "webapp-*"
  sort: name
  sort_end: -10
register: old_ami_result

ec2_ami:
  region: "{{ region }}"
  image_id: "{{ item.ami_id }}"
  delete_snapshot: yes
  state: absent
with_items: old_ami_result.results
ignore_errors: yes

---

roles/delete-old-launch-configurations/tasks/main.yml

lc_find:
  region: "{{ region }}"
  name_regex: "webapp-.*"
  sort: yes
  sort_end: -10
register: old_lc_result

ec2_lc:
  region: "{{ region }}"
  name: "{{ item.name }}"
  state: absent
with_items: old_lc_result.results
ignore_errors: yes

#!/usr/bin/python



roles/delete-old-launch-configurations/library/lc_find.py
import json
import subprocess
def main():
    argument_spec = ec2_argument_spec()
    argument_spec.update(dict(
            region = dict(required=True,
                aliases = ['aws_region', 'ec2_region']),
            name_regex = dict(required=False),
            sort = dict(required=False, default=None, type='bool'),
            sort_order = dict(required=False, default='ascending',
                choices=['ascending', 'descending']),
            sort_start = dict(required=False),
            sort_end = dict(required=False),
        )
    )
    module = AnsibleModule(
        argument_spec=argument_spec,
    )
    name_regex = module.params.get('name_regex')
    sort = module.params.get('sort')
    sort_order = module.params.get('sort_order')
    sort_start = module.params.get('sort_start')
    sort_end = module.params.get('sort_end')
    lc_cmd_result = subprocess.check_output(["aws", "autoscaling", "describe-launch-configurations", "--region",  module.params.get('region')])
    lc_result = json.loads(lc_cmd_result)
    results = []
    for lc in lc_result['LaunchConfigurations']:
        data = {
            'arn': lc["LaunchConfigurationARN"],
            'name': lc["LaunchConfigurationName"],
        }
        results.append(data)
    if name_regex:
        regex = re.compile(name_regex)
        results = [result for result in results if regex.match(result['name'])]
    if sort:
        results.sort(key=lambda e: e['name'], reverse=(sort_order=='descending'))
    try:
        if sort and sort_start and sort_end:
            results = results[int(sort_start):int(sort_end)]
        elif sort and sort_start:
            results = results[int(sort_start):]
        elif sort and sort_end:
            results = results[:int(sort_end)]
    except TypeError:
        module.fail_json(msg="Please supply numeric values for sort_start and/or sort_end")
    module.exit_json(results=results)
from ansible.module_utils.basic import *
from ansible.module_utils.ec2 import *
if name == 'main':
    main()

When these roles are used together, Ansible will maintain a history of 10 AMIs and 10 Launch Configurations prior to the latest one of each. This will provide our rollback capability; in the event that you wish to roll back to an earlier deployed version of your application, you can update the active Launch Configuration in your Auto Scaling Group settings and replace your instances by terminating them in batches. Auto Scaling will start up new instances with your specified launch configuration in order to fulfill the desired instance count.

Win!

Now that we have a completed playbook to handle deployments of our application to EC2 Auto Scaling, all that remains is to hook it up to your existing systems to invoke it whenever you want a new deploy to occur. We'll cover that in a later blog post.

All the code from this article is available on GitHub.