Amazon Web Services Guide

    Requirements for the AWS modules are minimal.

    All of the modules require and are tested against recent versions of boto. You’ll need this Python module installed on your control machine. Boto can be installed from your OS distribution or python’s “pip install boto”.

    Whereas classically ansible will execute tasks in its host loop against multiple remote machines, most cloud-control steps occur on your local machine with reference to the regions to control.

    In your playbook steps we’ll typically be using the following pattern for provisioning steps:


    Authentication with the AWS-related modules is handled by eitherspecifying your access and secret key as ENV variables or module arguments.

    For environment variables:

    1. export AWS_ACCESS_KEY_ID='AK123'
    2. export AWS_SECRET_ACCESS_KEY='abc123'

    For storing these in a vars_file, ideally encrypted with ansible-vault:

    Note that if you store your credentials in vars_file, you need to refer to them in each AWS-module. For example:

    1. - ec2
    2. aws_access_key: "{{ec2_access_key}}"
    3. aws_secret_key: "{{ec2_secret_key}}"
    4. image: "..."


    The ec2 module provisions and de-provisions instances within EC2.

    An example of making sure there are only 5 instances tagged ‘Demo’ in EC2 follows.

    In the example below, the “exact_count” of instances is set to 5. This means if there are 0 instances already existing, then5 new instances would be created. If there were 2 instances, only 3 would be created, and if there were 8 instances, 3 instances wouldbe terminated.

    What is being counted is specified by the “count_tag” parameter. The parameter “instance_tags” is used to apply tags to the newly createdinstance.:

    The data about what instances are created is being saved by the “register” keyword in the variable named “ec2”.

    2. - hosts: localhost
    3. connection: local
    4. gather_facts: False
    6. tasks:
    8. - name: Provision a set of instances
    9. ec2:
    10. key_name: my_key
    11. group: test
    12. instance_type: t2.micro
    13. image: "{{ ami_id }}"
    14. wait: true
    15. exact_count: 5
    16. count_tag:
    17. Name: Demo
    18. Name: Demo
    19. register: ec2
    21. - name: Add all instance public IPs to host group
    22. add_host: hostname={{ item.public_ip }} groups=ec2hosts
    23. loop: "{{ ec2.instances }}"

    With the host group now created, a second play at the bottom of the same provisioning playbook file might now have some configuration steps:

    Once your nodes are spun up, you’ll probably want to talk to them again. With a cloud setup, it’s best to not maintain a static list of cloud hostnamesin text files. Rather, the best way to handle this is to use the ec2 dynamic inventory script. See Working With Dynamic Inventory.

    This will also dynamically select nodes that were even created outside of Ansible, and allow Ansible to manage them.

    See for how to use this, then return to this chapter.

    Tags And Groups And Variables

    When using the ec2 inventory script, hosts automatically appear in groups based on how they are tagged in EC2.

    For instance, if a host is given the “class” tag with the value of “webserver”,it will be automatically discoverable via a dynamic group like so:

    1. - hosts: tag_class_webserver
    2. tasks:
    3. - ping

    Using this philosophy can be a great way to keep systems separated by the function they perform.

    In this example, if we wanted to define variables that are automatically applied to each machine tagged with the ‘class’ of ‘webserver’, ‘group_vars’in ansible can be used. See Splitting Out Host and Group Specific Data.

    Similar groups are available for regions and other classifications, and can be similarly assigned variables using the same mechanism.

    Autoscaling with Ansible Pull

    Amazon Autoscaling features automatically increase or decrease capacity based on load. There are also Ansible modules shown in the cloud documentation thatcan configure autoscaling policy.

    When nodes come online, it may not be sufficient to wait for the next cycle of an ansible command to come along and configure that node.

    To do this, pre-bake machine images which contain the necessary ansible-pull invocation. Ansible-pull is a command line tool that fetches a playbook from a git server and runs it locally.

    One of the challenges of this approach is that there needs to be a centralized way to store data about the results of pull commands in an autoscaling context.For this reason, the autoscaling solution provided below in the next section can be a better approach.

    also contains a very nice feature for auto-scaling use cases. In this mode, a simple curl script can calla defined URL and the server will “dial out” to the requester and configure an instance that is spinning up. This can be a great wayto reconfigure ephemeral nodes. See the Tower install and product documentation for more details.

    A benefit of using the callback in Tower over pull mode is that job results are still centrally recorded and less information has to be sharedwith remote hosts.

    Ansible With (And Versus) CloudFormation

    CloudFormation is a Amazon technology for defining a cloud stack as a JSON document.

    Ansible modules provide an easier to use interface than CloudFormation in many examples, without defining a complex JSON document.This is recommended for most users.

    However, for users that have decided to use CloudFormation, there is an Ansible module that can be used to apply a CloudFormation templateto Amazon.

    When using Ansible with CloudFormation, typically Ansible will be used with a tool like Packer to build images, and CloudFormation will launchthose images, or ansible will be invoked through user data once the image comes online, or a combination of the two.

    Please see the examples in the Ansible CloudFormation module for more details.

    AWS Image Building With Ansible

    Many users may want to have images boot to a more complete configuration rather than configuring them entirely after instantiation. To do this,one of many programs can be used with Ansible playbooks to define and upload a base image, which will then get its own AMI ID for usage withthe ec2 module or other Ansible AWS modules such as ec2_asg or the cloudformation module. Possible tools include Packer, aminator, and Ansible’sec2_ami module.

    Generally speaking, we find most users using Packer.

    See the Packer documentation of the Ansible local Packer provisioner and .

    If you do not want to adopt Packer at this time, configuring a base-image with Ansible after provisioning (as shown above) is acceptable.

    Ansible ships with lots of modules for configuring a wide array of EC2 services. Browse the “Cloud” category of the moduledocumentation for a full list with examples.

    See also