news
Fedora and Red Hat Leftovers
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Red Hat ☛ Improved failure reports on Red Bait OpenShift with the event-driven diagnostic operator
Imagine this: It's late. A major incident just rocked your production environment. Teams are scrambling, alarms are flying, and after some emergency actions, the site is back up. Crisis averted?
Not really.
When you finally sit down to figure out what actually happened, the most important thing—the logs—are gone. Overwritten. Lost in the rush. No clear trigger, no breadcrumbs, just a black hole where your root cause should be.
It's like showing up at a crime scene after the evidence has been wiped clean.
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Copr: Throwing 224 Cores at rpmbuild
In Fedora Copr, we maintain a special tier of build machines known as High-Performance Builders (or as we call them internally, “powerful builders”).
Historically, gaining access to these machines required some manual intervention. Maintainers had to write to us, and we would enable them for specific projects or packages based on matching regular expressions. I’m happy to say those days of manual labor are over. This process is now entirely automated thanks to rpmeta (expect a dedicated blog post on this soon).
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Red Hat ☛ Red Hat Ansible development workspaces for governed automation content creation
Onboarding a new automation developer is rarely quick. Day 1 is paperwork. On day 10, the laptop arrives. On day 20, the IDE and tools are installed. On Day 30, repository access and permissions are finally sorted out, and it can be weeks before a single playbook gets written.
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Red Hat Official ☛ Unify IT workflows at scale with the new automation orchestrator for Ansible Automation Platform
For IT teams that have already put trusted, governed automation into practice with Ansible Automation Platform, this add-on delivers a new set of tools for orchestrating automation at scale. Automation orchestrator simplifies complex workflow management in Ansible Automation Platform. The visual canvas (Figure 1) gives teams a clearer, more intuitive way to coordinate advanced orchestration without touching the proven automations already in production.
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Red Hat Official ☛ How a global financial messaging network secured millions of containers and defeated alert fatigue
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Red Hat Official ☛ From fragmented to flawless: Unifying the AI development lifecycle [Ed: IBM Red Hat pushing slop]
Developing robust AI solutions demands managing a complex ecosystem of data, experiments, and models. One of the primary hurdles data science teams face is the fragmentation of their initial workflows. To build effective and accurate models, teams must be able to seamlessly connect multiple data sources to enrich, query, visualize, and annotate datasets. When data operations are disconnected, managing and preparing high-quality data can become a manual, error-prone bottleneck.