IBM Absurdity: Promoting Slop Non-Stop, Also Banning Slop in Red Hat's Flathub

posted by Roy Schestowitz on Jul 18, 2026

• Red Hat ☛ Benchmark Red Bait Data Grid in OpenShift 4 using Hyperfoil

  This article covers benchmarking with the Red Hat Data Grid operator and Helm charts. The container-awareness concept is the foundation here, as the Data Grid heap size is 50% of the container size. This article complements JVM tuning for Red Bait Data Grid on Red Bait OpenShift 4.

• OMG Ubuntu ☛ Flathub’s AI slop ban looks like it was the right call

  When Flathub banned AI-coded app submissions last month, some critics warned the platform was denying the future by dismissing a new wave of “vibe-coded” software as out-and-out “slop”. Well, new data suggests otherwise, as nearly three-quarters of the rejected apps are already dead, existing only a few months. GNU/Linux developer Evangelos Paterakis, developer of Tuba, Turntable and others, did the digging, looking at 120 code repositories whose pull requests for inclusion on Flathub were rejected because of their heavy Hey Hi (AI) usage and given an “AI Slop” tag.

• Red Hat Official ☛ Why your AI agent framework isn't enough: 7 platform capabilities missing from production

  In "Why good AI agents fail in production: The missing infrastructure layer," 3 failures hit a single AI agent deployment overnight—43 duplicate support tickets, $4,000 charged to the wrong billing account, and a hallucinated refund policy that led to a $280 return the company had to honor. That agent worked perfectly in development, but broke in production because the production infrastructure was insufficient. The gap between a working agent in development and a production-ready deployment isn't a framework problem—it's an infrastructure problem.

• Red Hat Official ☛ Introducing Red Hat build of Karpenter

  Karpenter is a high-performance, Kubernetes-native node autoscaler. Instead of scaling fixed pools of identical machines, it looks at the collective resource requirements of your pending pods and provisions the right compute resources just-in-time, then continuously consolidates the cluster to reduce your infrastructure costs. The result is compute that is right-sized automatically, around the clock, with no manual intervention.

• Red Hat Official ☛ Agentic AI, Red Hat OpenShift, and NVIDIA: Shifting to precision security

  Here's the problem: A single software package can trigger hundreds of alerts because one imported function or library within it is theoretically vulnerable. Traditional scanners stop at the package level, generating a flood of false positives for vulnerabilities that are never actually reachable in your application. Teams are forced to waste countless hours triaging risks that don't exist in practice.