The anatomy of automation execution environments

September 12, 2022 by Anshul Behl

anatomy of EE blog

Red Hat Ansible Automation Platform 2 introduced  major architectural changes, like automation mesh and automation execution environments, that help extend Ansible automation across your organization in a flexible manner, providing a single solution to all your organizational and hybrid cloud automation needs.

Automation execution environments are container images that act as Ansible runtimes for automation controller jobs. Ansible Automation Platform also includes a command-line tool called ansible-builder(execution environment builder)that lets you create automation execution environments by specifying Ansible Content Collections and Python dependencies.

In general, an automation execution environment includes:

  • A version of Python.
  • A version of ansible-core.
  • Python modules/dependencies.
  • Ansible Content Collections (optional).

In this blog, I will take you through the inner workings of ansible-builder and how all the above requirements are packaged inside automation execution environments and delivered as part of Ansible Automation Platform.


A tale of two ansible-builder packages

As all projects in Red Hat, ansible-builder follows an open development model and an upstream-first approach. The upstream project for ansible-builder is distributed as a Python package, and then packaged into an RPM for Ansible Automation Platform downstream.This also means that there are different ways to install the upstream package and the downstream ansible-builder.

NOTE: To get the downstream packages, you must subscribe to Ansible Automation Platform repos from Red Hat.


pip3 install ansible-builder


dnf install ansible-builder

This has sometimes led to confusions among users, as customers of Ansible Automation Platform can also install the Python package for free. There are minor differences between both upstream and downstream packages that you should understand before diving deeper into building automation execution environments.

As mentioned earlier, automation execution environments are container images that act as Ansible runtimes and ansible-builder is quite similar to generally available container engines such as Podman and Docker. So like any other container engine, the concept of building an image starts with a base image; that is where the upstream and downstream packages for ansible-builder differ. The base images used in upstream ansible-builder (Python package) as predefined constants are as follows:


Base images in the downstream package are as follows:


Upstream base images are available through Red Hat, while the downstream ones come from Red Hat Ecosystem Catalog(, which requires authentication with a Red Hat account. The other difference in these images is that upstream ones use CentOS image as the base image while the downstream ones use Red Hat Universal Base Image (UBI). UBI offers greater reliability, security, and performance for official Red Hat container images compared with CentOS images.

One commonality for the upstream and downstream packages is that they both allow image configuration through an automation execution environment specification file called execution-environment.yml.

Whether you are an Ansible Automation Platform customer or a community user of ansible-builder, you can use UBI images as base images or the CentOS images for your automation execution environments based on the package or by  passing a different set of base images to your automation execution environment specification file.


Why does the ansible-builder package have two base images?

Continuing from the previous section that introduce the upstream and downstream base images for ansible-builder, there are two arguments that specify which images to use:

  • The EE_BASE_IMAGE build argument specifies the parent image for the automation execution environment.
  • The EE_BUILDER_IMAGE build argument specifies the image used for compiling type tasks.

For most container images, you generally only need one base image on top of which you add different instructions, also known as build steps, to create your final container image.

However, the base automation execution environment (ee-minimal) is built using the multi-stage build concept of containers. The EE_BUILDER_IMAGE build argument serves as the intermediary step to install Collections and build dependencies to keep the base image size as low as possible.

Let’s take an example: Suppose your Ansible Content Collection depends on a Python package that needs to be compiled using python-dev package (e.g. NumPy). Because python-dev is a compile time dependency, you don’t necessarily need it in the final package (you just need the NumPy package). You wouldn’t want to include python-dev in the final image to keep the image size as low as possible. For this purpose, the EE_BUILDER_IMAGE is used to build dependencies and then copy over only the package wheels needed for the final automation execution environment.


Does this matter if I want to build a custom automation execution environment?

In most cases it doesn’t matter. When you build your automation execution environment using ansible-builder, you just need EE_BASE_IMAGE and not EE_BUILDER_IMAGE. However, you should understand how a compile time binary dependency is applied in the execution-environment definition file called bindep.txt. For the above example, if you need to install the NumPy Python package as a dependency for your Collection on UBI8, you specify the bindep.txt and requirements.txt as follows:


python38-devel [compile platform:rhel-8] #compile time dependency



There will be instances where the configuration in the automation execution environment specification isn’t reflected or errors occur when you’re building the automation execution environment. In these instances, it's important to understand the role for the EE_BUILDER_IMAGE. The next section explains this in more detail.


Automation execution environment design

diagram picture of automation execution environment design

Click to open image in new tab

The above diagram outlines how automation execution environments are designed. I have mentioned the upstream image name and the downstream counterparts in the same boxes.

For reference, CentOS 8 and UBI8 (for downstream) serve as the base images for the python-base container image, which acts as the image for running python-based projects, hence it bundles a version of Python that is supported by the ansible-core package (python 3.8 for reference).

This python-base image serves as the base image for both the python-builder image as well as the ansible-runner (ee-minimal downstream) image. To summarize the purpose of python-builder and ansible-builder images, they build Python projects such as ansible-core and any Collections that are dependent on Python. For instance, if your Collection relies on Python dependencies for which wheels need to be built on the machine itself, they are built on the python-builder image.

Finally, the ansible-runner (ee-minimal downstream) image includes a version of the ansible-core package. The ansible-builder image works in conjunction with this image to build Python wheels, so that the final automation execution environment size is minimal by only keeping things that are necessary to run your required automation. custom-ee1 and custom-ee2 in the diagram represent any custom automation execution environments that can be created using ansible-runner (ee-minimal downstream) and the ansible-builder image.


Verifying your base images

To start building your custom automation execution environments, you should first verify which EE_BASE_IMAGE and EE_BUILDER_IMAGE are used in ansible-builder by default. To verify, first create an empty automation execution environment definition file called execution-environment.yml

touch execution-environment.yml

Then create a build context from the empty definition file by running this command in the same directory where you created the empty definition file:

ansible-builder create

This will create a context directory in your working directory which includes a Containerfile. Opening the Containerfile shows which images are set as the BASE and BUILDER images and tells you which ansible-builder you are using, the upstream or the downstream one. For instance, if you open the Containerfile created through the above process and a pip install of ansible-builder, you see the following content:



USER root


USER root
COPY --from=builder /output/ /output/
RUN /output/install-from-bindep && rm -rf /output/wheels

In the first two lines you can observe that the images point to the upstream images. If you do the same process on the downstream install of ansible-builder, you find the downstream images in a similar Containerfile.


Using the ansible-builder context

The context building is an important aspect of ansible-builder. You can use the context to change the Containerfile and customize your automation execution environments to your needs. You can use this context and the knowledge of multi-stage builds using BUILDER and BASE images to build an automation execution environment in a disconnected environment. The following shows an execution-environment definition that pulls the BUILDER and BASE images from a private automation hub instance:

# cat execution-environment.yml 
version: 1
  EE_BASE_IMAGE: 'automation-hub.demolab.local/ansible-automation-platform-22/ee-minimal-rhel8:latest'
  EE_BUILDER_IMAGE: 'automation-hub.demolab.local/ansible-automation-platform-22/ansible-builder-rhel8:latest'

  python: requirements.txt

And the contents of the requirements.txt file are as follows:

# cat requirements.txt 

Let’s create a context for the above definition file, execution-environment.yml:

# ansible-builder create
Complete! The build context can be found at: /root/disconnected_ee/context

The following issues may arise when building an automation execution environment in a disconnected environment (this example takes into account the building of a downstream image):

  • Cannot reach the external yum repositories.
  • Cannot pull Python dependencies from an external PyPI server, so using an internal PyPI proxy when building an automation execution environment.
  • (Optional) SSL certificate issues when pulling from internal PyPI mirror.

Firstly, create a pip.conf that points to the local mirror:

# cat context/pip.conf 
index-url = https://nexus-nexus.apps.celeron.demolab.local/repository/pypi-proxy/simple/

You add the above pip.conf file and the certificate to the context/ folder for the targeted automation execution environment creation to add these files inside your custom execution-environment.

Using the multi-stage build knowledge and context editing, edit the Containerfile. Note the sections marked in bold text as well as some comments. These are the changes to build an automation execution environment in a disconnected fashion.

# cat Containerfile 
ARG EE_BASE_IMAGE=automation-hub.demolab.local/ansible-automation-platform-21/ee-supported-rhel8:latest
ARG EE_BUILDER_IMAGE=automation-hub.demolab.local/ansible-automation-platform-21/ansible-builder-rhel8:latest

USER root

ADD _build /build
WORKDIR /build

ADD _build/requirements.txt requirements.txt
RUN ansible-builder introspect --sanitize --user-pip=requirements.txt --write-bindep=/tmp/src/bindep.txt --write-pip=/tmp/src/requirements.txt

####### Changes to create EE in a disconnected environment
# Remove ubi repo which tries to reach external links
RUN rm -f /etc/yum.repos.d/ubi.repo
# Add pip.conf for internal pypi proxy
ADD pip.conf /etc/pip.conf
# Add CA certificate and update trust
ADD demolab-ca.crt /etc/pki/ca-trust/source/anchors/demolab-ca.crt
RUN update-ca-trust
####### This marks the end of edits for the builder stage

RUN assemble

USER root
COPY --from=builder /output/ /output/

####### Changes to create EE in a disconnected environment
# Remove ubi repo which tries to reach external links
RUN rm -f /etc/yum.repos.d/ubi.repo
# Add pip.conf for internal pypi proxy
ADD pip.conf /etc/pip.conf
# Add CA certificate and update trust
ADD demolab-ca.crt /etc/pki/ca-trust/source/anchors/demolab-ca.crt
RUN update-ca-trust
####### This marks the end of edits for the main image

RUN /output/install-from-bindep && rm -rf /output/wheels

If you look closely in the above Containerfile, you can notice the additions that fix all the issues previously mentioned in both the BUILDER and the BASE image stages because both images use this information to pull and build Python dependencies.

Understanding what happens in each stage helps you understand where to edit your Containerfile, and at which stage, allowing you to make endless customizations to your custom automation execution environments.

Finally let’s build the above execution-environment with the following command:

podman build -f context/Containerfile -t disconnected_ee:1.0

When the build succeeds, you should see a message like this:

--> 2316db485a1
Successfully tagged localhost/disconnected_ee:1.0


Looking forward

Our ultimate goal is to make the developer experience as seamless as possible for customers. Ansible engineering teams are working on enhancements to the automation execution environment building experience, with several improvements already in the planning stage. Until those enhancements are available, this blog should help you tackle any challenges around the process of building automation execution environments. Following the upstream first model means you can also participate in community discussions and provide your thoughts and feedback through IRC. Please follow the link here to join us. One of the main enhancements to the automation execution environment experience is being discussed in this GitHub pull request, so you can participate in the GitHub discussions as well.


Next Steps

This blog assumed some initial knowledge about automation execution environments and ansible-builder. You can find more information in the following materials:


Automation execution environments


Anshul Behl

Anshul is a Technical Marketing Manager at Red Hat, where he bring his software development and QE experience to increase Ansible Automation Platform's adoption experience for customers by producing technical content on all aspects of the product.

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