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Contributing.md

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Contributing to ML Platform on EKS

Your interest in contributing to ML Platform on EKS is greatly appreciated! We embrace contributions from the community to enhance and refine our project. To ensure a seamless and collaborative contribution experience, please adhere to the following guidelines.

Getting Started

Begin by forking the repository on GitHub and then cloning your forked copy to your local machine.

Making Contributions

When making contributions:

Branching

Create a new branch for your changes with a descriptive name that mirrors the purpose of your contribution (e.g., feature/add-new-feature).

Commit Messages

Compose clear and concise commit messages:

  • Prefer the present tense (e.g., "Add feature" instead of "Added feature").
  • Offer context and insights about your changes.

Testing

Include tests if relevant and ensure that any pre-existing tests pass.

Pre-commit Hooks

This repository utilizes pre-commit hooks to enhance code quality and minimize errors. These hooks automatically perform checks before commits, ensuring higher reliability. Install pre-commit using pip install pre-commit if not already done. Next, navigate to the root directory of the project and set up the hooks via pre-commit install. As you make changes to code or files, add modified files using git add. Finally, commit changes in the usual way using git commit -m "Your commit message". If any issues arise based on formatting, linting, or other criteria, commits are paused until addressed. This approach guarantees uniform code quality and diminishes the risk of errors.

Submitting Contributions

To submit your contributions:

  1. Push your changes to your forked repository.
  2. Forge a pull request (PR) from your branch to the main branch of the original repository.
  3. Furnish your PR with an informative title and a comprehensive description elucidating your changes and their significance.

Code Review

Anticipate feedback from maintainers and fellow contributors. Address any comments and iterate on your work. Maintain a constructive and respectful demeanor throughout the code review process.

Communication

Stay engaged through our community forum or chat if available. For major changes, it's prudent to discuss them before embarking on substantial contributions.

License

By participating in this project, you acknowledge that your contributions are subject to the terms of the Project License.

Your contributions are immensely valued, and we eagerly anticipate collaborating with you!

TODOs

General:

  • Test GitHub actions for automatic deployment.
  • Add secrets to GitHub actions for secure handling of sensitive information.

Security and User Management:

  • Enhance cluster security to limit public access to sensitive components.

JupyterHub Improvements:

  • Health check for JupyterHub ALB is currently failing

ExternalDNS Setup:

  • Limit hosted zone in ExternalDNS for better control over DNS records.

AWS EKS Cluster:

  • Set EKS cluster to not be publicly accessible to improve security.