In this brief blog, we will introduce the CI/CD philosophy, and our practices.
Back to years ago, our team has tried CI/CD tools including but not limited to travis, GitLab runners, etc. Until recently, we adopted GitHub actions as our current choice.
As these tools evolves (or your choice changes), the code CI/CD pipelines, in the form of YAML files or manual configure pipelines, has to be refactored to fit new tools.
This post summarizes our practices, experience, and philosophy for using containers in development and DevOps.
Since container technology became widely adopted in software development and application delivery, it has introduced clear improvements over traditional approaches in several areas.
Whether developers work on local machines such as Linux (Ubuntu/CentOS), Windows (WSL), or macOS (Intel/Apple Silicon), in build environments (for example CI/CD pipelines), or in runtime environments (for example production), they can use containers to standardize environments. This eliminates coordination issues caused by differences in versions and configurations, and greatly reduces the classic "it works on my machine" problem.
Welcome to LabNow!
We aim at providing a set of foundation building blocks helping AI and Software Engineers for their AI/Data and development work.
Please visit our GitHub Repo and read the README files in each sub-folder as we are updating the docs.