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The idea of a "CareTaker" for git centeric network operations

Many organizations have embraced, or are beginning to embrace the configuration management of their network devices through code. A common pattern that I’ve come across consists of:

  1. A git repository for scrubbed, last-known-good-configs
  2. Another git repository that holds the infrastructure as code (IaC)

Operators create feature branches off of the second repo, and submit pull-requests. These changes are then subject to various tests (manual or automatic) before being approved and merged into the master branch, which then gets deployed onto the end points.

But the idea of GitOps goes further than that – it uses tools to compare the actual production state of your endpoints with what’s under source control and then it tells you when they don’t match. This post introduces the idea of a “CareTaker” that detects out-of-band (OOB) changes made to the network endpoints and alerts the operator to make a manual decision.

This blog post will present an implementation of such a “CareTaker” using an Ansible collection. A demo of this implementation is seen here:

Steady State Operations

The steady state operations might look as follows: Steady state Git Ops

The operator creates a pull request against the IaC repository and after this is merged, Ansible pushes the configuration to the end points.

An OOB change is introduced

During production operations, there might be situations where an engineer might have to go in and make changes manually to the endpoints. Possibly due to:

The above two are just 2 potential examples. There might be numerous valid reasons to make these OOB changes.

The potential also exists for someone making an incorrect change. Maybe an engineer who is not very familiar with the operational protocols of the organization.

TL;DR an OOB change has now been introduced into the network and running configs are no longer in synch with the last-known-good configurations.

Impact of the OOB on Git centric operations

Let’s say the OOB change was made to the data-model under IaC control - to say shutdown a bgp neighbor to address unreachable Autonomous Systems through that neighbor. A very valid production reason to go implement the fix. With this fix in place, the IaC model no longer reflects what’s running. Nor does the last-known-good config match what’s running. Say, the IaC repo had the BGP configs for a router defined as follows:

  bgp_as: 65000
  log_neighbor_changes: true
    - neighbor: "{{ remote_public_ip  }}"
      remote_as: 65000
    - prefix:
      masklen: 24
    - prefix:
      masklen: 24

At this point, say, an engineer who is unaware of this fix, tries to advertise a new network to this IaC; by adding a new network to the list of advertised networks

    - prefix:
      masklen: 24

This change, might slip through normal testing because everything is valid about it (syntax, value of network IP etc). If this change gets propagated to the network, it will revert the manual fix put in place earlier and re-introduce the issue.

Another scenario to consider for the impact may be configurations that are not being tracked by the IaC. The above IaC is only tracking BGP configurations. However, there might be changes made on the device (say to the IGP) that can potentially impact the effect of this configuration. While this scenario is less likely, you would want your automation systems to make sure that the running configurations at least match your last-known-good. If this is not the case, it should alert you about an OOB configuration and allow the operator to manually decide whether the last-know-good config should be replaced with running or vice versa before pushing their changes onto production.


Captain Kathryn Janeway : Did you ever consider allowing the
Ocampa to care for themselves?
The Caretaker : [laughs pitifully] They're children.

                                     - Star Trek Voyager, S1E1

To address this, I created a demo collection called the caretaker:

This is an illustrative demo collection and not to be used in production. Currently, it is only implemented for EOS devices.

The collection uses a role that basically compares the configurations from the last-known-good configuration repo with the current running configs of the devices. If it detects a difference, it simply fails. That’s it! Very simple.

How do you invoke this in your playbook?

# deploy_bgp.yml
- name: Deploy IaC configs to BGP routers
  hosts: arista
  gather_facts: no
    - name: Invoke Caretaker
        name: termlen0.caretaker.caretaker


    - name: Configure the routing protocol
        config: "{{ bgp_config  }}"
        operation: replace

So the idea here is that caretaker would act as a meta task that is always included in every deployment playbook. This way, the engineer implementing the change can have absolute confidence that the configuration being deployed will only succeed if there are no OOB changes on the network devices.

Using Caretaker with Tower

The simplicity of this collection lies in the fact that it is easy to add to existing playbooks. Using Ansible Tower’s workflows, the deployments can now become a lot more intelligent.

Tower WorkFlow

The above workflow uses deploy playbook with the caretaker collection. During normal operations - meaning, no OOB changes - the playbook would run normally, succeed, and the new running configs will be backed up to the last-known-good config repo (green path).

The playbook will fail if caretaker detects OOB changes. It then uses approval nodes to alert the operator. A human needs to intervene at this point and decide whether the running configs should be replaced with the last-known-good configs before deploying the new change or alternately, the last-known-good configs should be updated before the changes are made.

Some additional notes

Using collections with Ansible Tower

If you are new to Ansible collections this blog post is a good place to understand how to use collections with Ansible Tower.

What are approval nodes?

Bianca has a detailed blog post on Approval Workflows

Integration with GitHub

Tower workflows can be invoked via webhooks. So for our use case example, the operator is simply making a Pull Request to the BGP data-model and once merged, it kicks off the Tower workflow.

Workflow Webhook

Tim Appnel has a 2-part in depth blog on using Web Hooks in Ansible Tower and is a great read for Git Ops in general.


Ansible Tower has so many built-in notification options. Tools like Slack are popular among teams and organizations that are embracing DevOps. For this demo, each time human attention is needed (for the approval nodes), the workflow sends a slack team notification:

Alt Text

Demo repository

The IaC repository used for this demo can be seen here:


Though the idea behind the blog is to highlight how a collection like caretaker can be used to increase confidence in Git centric operations, it also illustrates a secondary idea. About Ansible collections in general. This shows how higher abstractions of automation can now be bundled as a collection, ready to be consumed by playbooks.