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Five ways to get started with network automation

Five ways to get started with network automation

As many of you know, Red Hat Ansible Automation Platform is a highly flexible IT automation platform that can automate your Linux and Windows instances, your VMware private cloud, your AWS, Azure or Google public cloud, and even your security infrastructure.  Today I want to write about one of my favorite use-cases; using Ansible Automation Platform for network automation. It provides easy, highly customizable automation for your routers and switches so you can automate them just like any other IT infrastructure.

However, even though network automation has become increasingly popular, most organizations are still managing their network infrastructure manually by a CLI or GUI. Why is this? This manual CLI work often means that network engineers are reactive and constantly drowning with break-fix network issues because of manual mis-configurations, or the inability to implement change quickly and efficiently.

Because network engineers are so busy firefighting in their day job, they don't have time to look at a new activity like automating, even though automation will save them time and money in the long run. I fundamentally believe that network automation is not an all or nothing situation.  You need to adopt network automation in small increments so you can earn yourself, and your team more time.  In other words, start small and think big. I put together this video to help network engineers brainstorm five great use cases for network automation. This list is not exhaustive; there are many more use-cases that you can do with network automation, but this is meant to give network administrators an idea of what is possible.

If you're looking to learn more about a specific use-case, you can jump right to it:

  1. configuration backup and restore
  2. infrastructure awareness
  3. scoped configuration management
  4. operational state validation
  5. automated netops
  6. wrap up and next steps






Migrating from Python virtual environments to automation execution environments in Ansible Automation Platform 2

Migrating from Python virtual environments to automation execution environments in Ansible Automation Platform 2

Red Hat Ansible Tower (included in Ansible Automation Platform 1.x) used Python virtual environments to manage dependencies and implement consistent automation execution across multiple Red Hat Ansible Automation Platform instances. This method of managing dependencies came with its own set of limitations:

  • Managing Python virtual environments across multiple Ansible Tower instances. 
  • Confirming custom dependencies across Ansible Tower instances grew in complexity as more end-users interacted with it.
  • Python virtual environments were tightly coupled to the control plane, resulting in Operations teams bearing the majority of the burden to maintain them.
  • There were no tools supported and maintained by Red Hat to manage custom dependencies across Ansible Automation Platform deployments.

Ansible Automation Platform 2 introduced automation execution environments. These are container images in which all automation is packaged and run, which includes components such as Ansible Core, Ansible Content Collections, a version of Python, Red Hat Enterprise Linux UBI 8, and any additional package dependencies.

Why should you upgrade?

Ansible Automation Platform 2, announced at AnsibleFest 2021, comes with a re-imagined architecture that fully decouples the automation control plane and execution plane. The new capabilities enable easier to scale automation across the globe and allow you to run your automation as close to the source as possible without being bound to running automation in a single data center. It's more dynamic, scalable, resilient and secure compared to Ansible Automation Platform 1.2.

If you are an existing Red Hat customer using Ansible Automation Platform 1.2 (Ansible Tower 3.8), an important migration recommendation is to convert any custom Python virtual environments in your cluster to automation execution environments. This one-time effort opens the door to take advantage of the latest Ansible Automation Platform 2 capabilities and the ability to execute consistent automation across multiple platforms with lower long-term maintenance.

We will now explain this specific migration consideration and provide you with some best practices on how to migrate to automation execution environments.

The manual process of upgrading

As outlined in this document, the manual process of upgrading to automation execution environments would go something like this:

  1. Prerequisite is a running Ansible Automation Platform 1.2 cluster where customers have configured one or more custom Python virtual environments in addition to the default one.
  2. Use the awx-manage command line utility present on the Ansible Tower node to get the list of custom Python virtual environments using the list_custom_venvs subcommand.
  3. Run the awx-manage export_custom_venv command on each virtual environment to get the list of Python packages installed in that virtual environment.
  4. Check the association of a virtual environment using the awx-manage custom_venv_associations command. This list of associations/information will help customers make associations of new execution environments in the Ansible Automation Platform 2.x cluster.
  5. Filtering the above information manually and feeding the list of requirements from step 3 above to the execution environment builder (ansible-builder) to create necessary custom execution environment(s).

Looking at the above process there can be two enhancements to this flow, which would help customers adopt automation execution environments faster:

  1. Exported requirements from step 3 above can be compared with the list of Python packages already present in the automation execution environment that will serve as the base layer for the newly created ones. This will be helpful, because there are dependencies that will already be resolved by the base automation execution environment and it will help customers if they can focus on what's needed when they start creating automation execution environments for their clusters.
  2. Since we love Ansible, why not just automate the above process, right? :)

The automated process of upgrading

The intent of this section is to explain how you can automate this process using Ansible. We have a few example Ansible Content Collections and roles that can be used to achieve this automation. The playbook would look something like this at a high level:

  1. Pull the list of packages from all the custom Python virtual environments present on the Ansible Tower node in Ansible Automation Platform 1.2.
  2. Compare the package lists from step 1 with the package list in the automation execution environment you decide to use as basis (ansible-2.9 in our example), to find the packages that are not present in the base.
  3. List from step 2 can be fed to an Ansible Role that can automate the execution environment creation, keeping the base  as the one we did the comparison with in step 2.

Let's take an existing Ansible Automation Platform 1.2 setup that has two custom virtual environments, called custom-venv1 and custom-venv2, which both have their own list of Python packages:

# awx-manage export_custom_venv /opt/my-envs/custom-venv1/ -q
certifi==2021.10.8
charset-normalizer==2.0.10
enum34==1.1.10
future==0.18.2
idna==3.3
requests==2.27.1
solidfire-sdk-python==12.3.0.203
urllib3==1.26.8

# awx-manage export_custom_venv /opt/my-envs/custom-venv2/ -q
zabbix-api==0.5.4

We will use a role packaged in the redhat_cop.ee_utilities Collection called virtualenv_migrate, that is designed for this specific purpose and run that against the Ansible Tower node. Below is a sample playbook and inventory file respectively:

---
- name: Review custom virtualenvs and diff packages from base EE
  hosts: tower
  become: true
  vars:
    - venv_migrate_ee_python_list: []
  tasks:
    - name: Include venv_migrate role
      include_role:
        name: redhat_cop.ee_utilities.virtualenv_migrate
[tower]
ansibletower.demoredhat.com

[local]
localhost

[all:vars]
venv_migrate_default_ee_url="registry.redhat.io/ansible-automation-platform-21/ee-29-rhel8:latest"
registry_username=myRedHatID
registry_password=mypassword

The output of the playbook is shown below. It did the comparison as expected and gave us the list of packages from custom Python virtual environments that were not present in the base automation execution environment.

NOTE: The version based comparison for PIP packages is not included at this moment.

TASK [redhat_cop.tower_utilities.virtualenv_migrate : diff | Show the packages that are extra from default EEs in custom venvs.] ******************************************************************************
ok: [3.228.23.40 -> localhost] => {
    "msg": [
        {
            "/opt/my-envs/custom-venv1/": [
                "certifi",
                "charset-normalizer",
                "enum34",
                "future",
                "solidfire-sdk-python"
            ]
        },
        {
            "/opt/my-envs/custom-venv2/": [
                "zabbix-api"
            ]
        }
    ]
}

The above output can be directly passed to another Ansible Role in the same redhat_cop.ee_utilities Collection called ee_builder; its use case is to automate the execution environment creation process.

Briefly summing things up:

  • We ran a playbook against the Ansible Tower node to gather Python packages (from custom Python virtual environments) that are not in the base automation execution environment.
  • Output from above can help the creation of custom automation execution environments using the ee_builder role that automates execution environment creation.

Key takeaways

  • Using this new Ansible Role in combination with the ee_builder role can be used to automate the migration from custom virtual environments to automation execution environments.
  • These roles are currently part of a community project and not officially supported by Red Hat. However, they can provide details in the understanding of the migration process.