It is no secret that when we are writing software, tests are a critical component to ensure the code actually does what we say it does. It is so critical that most languages come with testing frameworks. JavaScript has testing frameworks such as mocha and jasmine. Go ships with its own testing capabilities provided by the testing package. And while writing tests in these languages is an accepted standard practice, all too often we forget that there is more to getting an application onto production than the app itself.
Dockerfiles play a big part in how we ship software at my company. We use them heavily in our build pipelines to run containerized jobs as well as the distribution mechanism to get the software onto our Kubernetes clusters. We like to say, "If it's code, we can test it," and that is no exception when it comes to writing Dockerfiles
.
A traditional approach to writing Dockerfiles
When tasked with writing a Dockerfile
, there are defined requirements that the Dockerfile
needs to satisfy. Binaries may be required to run linting tools, environment variables need to be set, and files have to exist at specific paths. Consider the Dockerfile
that was shown in an earlier blog post, Deploying Atlantis to Kubernetes with Azure DevOps:
FROM golang:1.13 as builder
RUN apt-get update \
&& apt-get install unzip
# Install terraform-bundle
RUN git clone \
--depth 1 \
--single-branch \
--branch "v0.12.0" \
https://github.com/hashicorp/terraform.git \
$GOPATH/src/github.com/hashicorp/terraform
RUN cd $GOPATH/src/github.com/hashicorp/terraform \
&& go install ./tools/terraform-bundle
# Download plugins
COPY terraform-bundle.hcl .
RUN terraform-bundle package -os=linux -arch=amd64 terraform-bundle.hcl
RUN mkdir /go/tmp \
&& unzip /go/terraform_*-bundle*_linux_amd64.zip -d /go/tmp
FROM runatlantis/atlantis:v0.11.1
ENV TF_IN_AUTOMATION="true"
ENV TF_CLI_ARGS_init="-plugin-dir=/home/atlantis/.atlantis/plugin-cache"
# Install Azure CLI
ARG AZURE_CLI_VERSION="2.0.74"
RUN apk add py-pip \
&& apk add --virtual=build gcc libffi-dev musl-dev openssl-dev python-dev make
RUN pip --no-cache-dir install azure-cli==${AZURE_CLI_VERSION}
# Install Terragrunt
ARG TERRAGRUNT_VERSION="v0.23.2"
RUN curl -L https://github.com/gruntwork-io/terragrunt/releases/download/${TERRAGRUNT_VERSION}/terragrunt_linux_amd64 \
&& -o /usr/local/bin/terragrunt \
&& chmod +x /usr/local/bin/terragrunt
# Copy plugins
COPY .terraformrc /root/.terraformrc
COPY --chown=atlantis:atlantis --from=builder /go/tmp /home/atlantis/.atlantis/plugin-cache
RUN mv /home/atlantis/.atlantis/plugin-cache/terraform /usr/local/bin/terraform
# Configure git
COPY .gitconfig /home/atlantis/.gitconfig
COPY azure-devops-helper.sh /home/atlantis/azure-devops-helper.sh
# Copy server-side repository config
COPY repository-config.yaml /home/atlantis/repository-config.yaml
CMD ["server", "--repo-config=/home/atlantis/repository-config.yaml"]
LABEL org.opencontainers.image.title="Atlantis Environment"
LABEL org.opencontainers.image.description="An environment to support executing Terragrunt operations with Atlantis"
LABEL binary.atlantis.version="v0.11.1"
LABEL binary.terragrunt.version=${TERRAGRUNT_VERSION}
LABEL binary.azure-cli.version=${AZURE_CLI_VERSION}
This Dockerfile
requires:
- Terraform plugins to support different types of infrastructure.
- The Terragrunt CLI.
- Two environment variables,
TF_IN_AUTOMATION
andTF_CLI_ARGS_init
. - Git configuration that points to an Azure DevOps helper script (and the script itself).
- A global configuration for repositories that use Atlantis.
To begin writing this Dockerfile
, knowing that we'll need to install terraform-bundle (using Go), as well as install the unzip
package to unzip the generated bundle, we could jump right into it and create a Dockerfile
:
FROM golang:1.13 as builder
RUN apt-get update \
&& apt-get install unzip
To verify that the base image exists and that the unzip package was successfully installed, we execute the docker run
command with an interactive terminal to explore the contents of the produced container.
$ docker build . -t testing:latest
$ docker run -it testing:latest
root@fb06cc45835c:/go# unzip
UnZip 6.00 of 20 April 2009, by Debian. Original by Info-ZIP.
We know the unzip
package successfully installed because after executing the binary, we get a response back that includes the version of the binary and the date it was built.
If the unzip
package did not install successfully, the container would throw an error stating that unzip
is an unknown command.
$ docker run -it testing:latest
root@fb06cc45835c:/go# unzip
bash: unzip: command not found
This cycle of adding commands into the Dockerfile
, building the image, running the container, and exploring the structure of the container would need to continue until we met all of the requirements. While this process will allow us to satisfy all of the requirements, much of the verification is manual. Besides, when the requirements change, as they tend to do, it can be incredibly challenging to have confidence that we didn't inadvertently break anything else by introducing a change.
A better way forward with Container Structure Test
Container Structure Test is a tool developed by Google that enables us to test the structure of a container. I'm not sure how they came up with the name, but what's important is that it removes the need to test Dockerfiles
manually!
Container Structure Test supports four different types of tests: command
, file existence
, file content
, and metadata
. Each type of test can validate a different aspect of a container. It does this by running the container for you, automatically, and testing whether or not the structure of the container meets the defined requirements in the test file.
NOTE: If you would like a deeper dive into the internals of Container Structure Test, the folks over at Google put together a blog post that explains the different types of tests in greater detail, as well as how to get the most out of the tool.
Writing a Dockerfile
When equipped with Container Structure Test, rather than creating a new Dockerfile
, adding commands, building the container, running the container, and manually exploring the container—we define the requirements upfront.
In the previous example, the first known requirement was that the unzip
package had to be present inside of the container. To define this requirement as a test case within Container Structure Test, we use acommand
test:
schemaVersion: 2.0.0
commandTests:
- name: unzip
command: unzip
args: ["-v"]
To test the Dockerfile
, pass the name of the built image along with the location of the test file to the container-structure-test
CLI.
NOTE: It's possible to save some keystrokes, as well as time, by combining the docker build
and container-structure-test test
commands so that every time the Dockerfile
changes, a new image is built and the test suite is run against the most recently built image.
$ docker build . -t testing:latest \
&& container-structure-test test --image testing:latest --config unzip-test.yaml
===================================
============= RESULTS =============
===================================
Passes: 1
Failures: 0
Duration: 443.548204ms
Total tests: 1
While it's possible to create a single test and then pass the test inside of your Dockerfile
(which is reminiscent of Test-Driven Development), another valid approach is to define all your requirements first and build the Dockerfile
from the test suite. As either is acceptable, whichever method makes the most sense for your style is the one you should use!
To complete our example of writing a test suite for the Atlantis container image, this is the completed test suite.
schemaVersion: 2.0.0
# Validate the environment contains the required tooling
commandTests:
- name: Atlantis
command: atlantis
args: ["version"]
- name: Terraform
command: terraform
args: ["version"]
expectedOutput: ["Terraform v0.12.24"]
- name: Terragrunt
command: terragrunt
args: ["--version"]
- name: Azure CLI
command: az
args: ["--version"]
# Validate the required configuration files exist
fileExistenceTests:
- name: Server Configuration
path: /home/atlantis/repository-config.yaml
shouldExist: true
- name: Azure DevOps Helper
path: /home/atlantis/azure-devops-helper.sh
shouldExist: true
- name: Terraform Plugin Cache
path: /home/atlantis/.atlantis/plugin-cache
shouldExist: true
# Validate checkpoint functionality is off
fileContentTests:
- name: Terraform Checkpoint Disabled
path: /home/atlantis/.terraformrc
expectedContents: ['disable_checkpoint = true']
# Validate container environment is configured as expected
metadataTest:
env:
- key: TF_IN_AUTOMATION
value: true
- key: TF_CLI_ARGS_init
value: -plugin-dir=/home/atlantis/.atlantis/plugin-cache
Integrating Container Structure Test into your workflow
While using Container Structure Test for local development can save a lot of time when first writing the Dockerfile
, the benefits don't stop there!
After creating the Dockerfile
, we now have defined a set of requirements that the Dockerfile
must adhere to. Having this set of requirements enables us to be able to run Container Structure Test at any point in the future and verify, automatically, that no regressions or unexpected changes occurred inside of the container. A software component that exists inside of a container image could change its version at any time, or even worse, be removed altogether. If you depend on specific components, and particular versions, add tests for them!
In the case of Atlantis, the maintainers are free to change the version of Terraform inside of the container at any time during their release cycle. Updating from Atlantis 0.12
to 0.13
should be trivial, but because the version of Terraform used to deploy infrastructure needs to be taken into consideration—we need to be made aware when the version changes.
schemaVersion: 2.0.0
- name: Terraform
command: terraform
args: ["version"]
expectedOutput: ["Terraform v0.12.21"]
This command test
will fail the test suite when the version of Terraform inside of the container changes from v0.12.21
. Now, upgrading Atlantis is as simple as bumping the version and re-running the test suite.
Integrating Container Structure Test into your workflow for developing Dockerfiles
automates much of the manual exploration that was previously required to verify the structure of the container. As a bonus, after the Dockerfile
is first built, we have a test suite that we can run every time we need to make a change to the Dockerfile
inside of our pipelines.