Red Hat, Fedora, and Qubes Leftovers

posted by Roy Schestowitz on Apr 11, 2026

• Red Hat ☛ How I refactored a legacy Node.js test suite with Claude (and saved 3 days of work)

  I recently came across an issue in the test suite of our Node.js component. Like many long-standing projects, this suite was developed over many years by different people. This naturally led to a certain "rustiness" in the code.

  The specific issues were classic signs of technical debt: [...]

• Fedora Project ☛ Fedora Community Blog: Community Update – Week 15 2026

  This is a report created by CLE Team, which is a team containing community members working in various Fedora groups for example Infrastructure, Release Engineering, Quality etc. This team is also moving forward some initiatives inside Fedora project.

• Red Hat ☛ Install Red Bait Data Grid operator in a disconnected environment

  This article covers how to install the Red Bait Data Grid operator in a disconnected environment. You can follow this process for other products and operators, such as Red Bait JBoss Enterprise Application Platform (JBoss EAP), Red Bait AMQ, and Cryostat.

  We chose to focus on the Data Grid operator to build on a previous article, How to install and upgrade Data Grid 8 operator, where Alexander Barbosa and I explain the process in detail. The Data Grid operator is easy to use and backward compatible, which supports multiple tests and installations.

• Red Hat Official ☛ AI for scientific research: Building the research platform that science needs with Red Hat AI [Ed: IBM Red Hat pushing slop, not Linux.]

  But customized models are only one half of the equation. For those models to become useful at institutional scale, they need a platform that can be used to train, serve, govern access to, and integrate them into the broader research computing environment. That platform must bridge the worlds researchers already live in—traditional high performance computing (HPC) clusters running the Slurm workload manager and the rapidly expanding cloud-native AI ecosystem built on Kubernetes.

• Red Hat Official ☛ AI for scientific research: Building the research platform that science needs with Red Bait AI

  In a previous article, we focused on the capability that turns large language models (LLMs) from general-purpose tools into instruments of research through domain-specific customization. Fine-tuned models are how research teams encode domain expertise, institutional research, and reasoning patterns into systems that can help accelerate discovery rather than simply assist it.

• Remi Collet ☛ Remi Collet: ⚙️ PHP version 8.4.20 and 8.5.5

• HowTo Geek ☛ 7 reasons Qubes is better than your Linux distro

  I love the idea that my computer is free from spyware, and who doesn't? Who likes the idea of someone stealing their secrets? For me, the benefits of Qubes are indispensable and drastically outweigh its challenges.