1. Overview
2. Usage
3. Options

A cookiecutter Terraform template for Azure modules or projects. This is a templated content to instantiate new Azure Terraform content that saves having to go through constructing boilerplate content for new projects.

The output from this cookiecutter template has the following features (some optional) basically confgured:

• Terraform related devcontainers devcontainer.
• Terraform enabled pre-commit.
• TFLint configured for Azure.
• Tenable terrascan.
• Bridgecrew Checkov.
• GitHub content including a workflow that includes linting and pre-commit.

This is opinionated and in fairly early stages of development

Install cookiecutter to do all the work.

First, get Cookiecutter and install other required libraries. Here is an example using a Python virtual environment in Linux:

mkdir ~/venvs
python3 -m venv ~/venvs/cookiecutter
source ~/venvs/cookiecutter/bin/activate
pip install pip setuptools --upgrade
pip install cookiecutter

Then run it against this repository:

cookiecutter https://github.com/tonyskidmore/cookiecutter-terraform

You'll be prompted for some values. Provide them, then a Terraform project will be created for you. See Options below for further details on what these values are.

Answer the prompts with your own options. For example, creating a Terraform Azure module for Machine Learning:

repo_name [repo_name]: terraform-azurerm-machine-learning
full_name [Your Name]: Tony Skidmore
github_username [Your GitHub username]: tonyskidmore
project_short_description [A short description of the project.]: Terraform module for Azure Machine Learning
Select license:
1 - BSD 2-Clause License
2 - BSD 3-Clause License
3 - MIT license
4 - ISC license
5 - Apache Software License 2.0
6 - GNU Lesser General Public License v3 or later (LGPLv3+)
7 - GNU Lesser General Public License v3 (LGPLv3)
8 - GNU Lesser General Public License v2.1 or later (LGPLv2+)
9 - GNU Lesser General Public License v2.1 (LGPLv2)
10 - no
Choose from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 [1]: 3
version [0.0.1]:
use_checkov [y]:
use_terrascan [y]: n
use_github [y]: y
year_from [2023]:
year_to [2023]:
devcontainer_certs []: 

Enter the project and take a look around:

cd terraform-azurerm-machine-learning/
ls

Create a git repository in GitHub and then push to it:

# git init
git add .
git commit -m "first commit"
git branch -M main
git remote add origin [email protected]:tonyskidmore/terraform-azurerm-machine-learning.git
git push -u origin main

The table below provides further details on how the prompted values are used. These are configured in the cookiecutter.json file.

Enterprise proxies, such as Zscaler, terminate and insert their own certificate chains into TLS traffic. This can cause certificate errors in applications, such as those used within a devcontainer. Specifying a path to a certificate file will cause the file to be copied to .devcontainer/certs in the created repo path and will subsequently get included in the generated docker container image.

For example enter ~/certs/zscaler.crt for that certificate to be included in the devcontainer image.

Note: ensure that the PEM encoded certificate file has a .crt extension for it be recognized correctly.

To test against a development branch use:

cookiecutter https://github.com/tonyskidmore/cookiecutter-terraform --checkout feature_branch