Thanks!

CloudDM has been evolving for several years. A large part of the codebase was written by our team through traditional development practices.

Over the past six months, we increased our investment in the project and started adopting AI-assisted development more extensively. The main reason is that database systems are becoming increasingly complex — supporting many different databases requires a huge amount of domain knowledge, and AI has become a useful tool to help us explore, implement, and validate these scenarios.

Our current workflow is mainly: AI-assisted implementation → human review → testing → iteration.

The goal is not to replace engineering judgment, but to help us move faster while keeping the quality under control.

For trying it out on a small project, we provide binaries, Docker images, and Kubernetes deployment options.

For a quick local setup, we recommend the Docker `alone` version. It includes the required metadata database, so after starting the container you only need to complete a simple initialization process.

The detailed installation guide is available in the project documentation: https://github.com/ClouGence/open-cdm