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Convert Cloudformation Templates to Terraform.

Project description

Python Latest Tests Coverage License


Cloudformation 2 Terraform

Convert your Cloudformation templates to Terraform.
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Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. Contact
  7. Acknowledgements

About The Project

cf2tf is a CLI tool that attempts to convert Cloudformation to Terraform. We say attempt because it's not really possible to make the conversion with 100% accuracy (currently) because of several reasons mostly around converting a Map value in Cloudformation to the correct value in HCL.

Getting Started

Prerequisites

Cloud-Radar requires python >= 3.7

Installation

cf2tf is available as an easy to install pip package.

pip install cf2tf

Usage

To convert a template to terraform.

cf2tf my_template.yaml

This above command will dump all the terraform resources to stdout. You might want to save the results:

cf2tf my_template.yaml > main.tf

If you prefer to have each resource in its own file then:

cf2tf my_template.yaml -o some_dir

If some_dir doesn't exist, then it will be created for you. Then each resource type will be saved to a specific file (variables.tf, outputs.tf etc.).

Roadmap

  • Better conversion of Cloudformation Maps to Terraform (Maps, Block and json)
  • Allow overides for specific resources
  • Handle more advanced Cloudformation parameter types like SSM/Secrets manager
  • Better handling of Recources/Properties that failed conversion
  • Only download files needed, not entire terraform source code (200MB)

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

This project uses poetry to manage dependencies and pre-commit to run formatting, linting and tests. You will need to have both installed to your system as well as python 3.9.

  1. Fork the Project

  2. Setup the environment.
    This project uses vscode devcontainer to provide a completly configured development environment. If you are using vscode and have the remote container extension installed, you should be asked to use the devcontainer when you open this project inside of vscode.

    If you are not using devcontainers then you will need to have python installed. Install the poetry, nox, nox_poetry and pre-commit packages. Then run poetry install and pre-commit install commands.

    Most of the steps can be found in the Dockerfile.

  3. Create your Feature Branch (git checkout -b feature/AmazingFeature)

  4. Commit your Changes (git commit -m 'Add some AmazingFeature')

  5. Push to the Branch (git push origin feature/AmazingFeature)

  6. Open a Pull Request

Contact

Levi - @shady_cuz

Acknowledgements

Project details


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