Fedora is the Linux distribution that I primarily utilize, as it offers a satisfactory balance between cutting-edge packages and stability. The release schedule is six-monthly, and you can expect the most recent version of the main packages, a level of innovation you can only find in one of the most up-to-date and stable operating systems. Being a data professional, I enjoy trying new software and staying abreast of the newest industry innovation.
Contributing to Fedora
After having used Fedora for more than a decade, I decided to dedicate some time and make a contribution to the project by joining the packager maintainers team. My primary goal is to help to create a good Linux distribution for data professionals (engineers, analytics, database, machine learning, etc.) by providing ready-to-use packages and dependencies for complex data deployments, data lakes, data pipelines, analytics tools, machine learning, and AI. I know it’s a big challenge, but it’s also a great job because I work with those tools as a data professional.
Fedora has a large number of talented people working on data-related applications. I am delighted to contribute with them, and it is also a great opportunity to learn.
My focus is on maintaining and contributing to packages related to data, but also to Python, Scala, databases, analytics, and ML/AI related tools. I’m already maintaining a couple of packages, and the whole thing is really fun, because it forces you to get to know each package well, understand how it works, how to build it, the dependencies, security, create the RPM, and keep it updated.
Being a data professional who prefers working on Linux, I’m concerned that the majority of Linux distributions fail to provide enough ready-to-use applications for data professionals. Being cutting-edge (and stable), the Fedora’s release cycle helps keep the data applications always updated and closed to the upstream version. I’ve been creating data packages for my own use cases, why not contribute to the community as well?