Tag: OpenShift AI
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OpenShift AI Platform Architecture, Component by Component (Red Hat Gen AI Series, Part 13)
A working map of Red Hat OpenShift AI, the meta operator, the DataScienceCluster, and the components you should actually turn on, with the serving change most tutorials miss.
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Red Hat AI Hybrid Cloud Deployment, and Where It Actually Runs (Red Hat Gen AI Series, Part 4)
Red Hat AI runs on bare metal, in your private cloud, on public cloud GPU instances and in air gapped sites. Here is how to place a self hosted GenAI project when its data cannot leave the building.
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RHEL AI vs RHEL vs OpenShift AI, and Where a Project Belongs (Red Hat Gen AI Series, Part 3)
RHEL, RHEL AI and OpenShift AI get confused constantly. One is an operating system, one runs a single model on one server, one runs many across a cluster. Here is how to pick the right one for a project, with the trade offs named.
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Red Hat AI Explained, and How RHEL AI, OpenShift AI and the Inference Server Fit (Red Hat Gen AI Series, Part 1)
Red Hat AI is not one product but three: RHEL AI, OpenShift AI and the AI Inference Server. Here is what each does, the open source thesis behind them, and where to start when you have used a hosted model API but never run your own inference.
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watsonx LLMOps on OpenShift, from Notebook to Promotion Gate (IBM Gen AI Series, Part 22)
How to run generative AI features in production on the IBM stack: watsonx.ai for models and governance, Red Hat OpenShift AI for pipelines and GPUs, and a promotion gate that refuses to ship a regression.
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VMware Private AI vs Red Hat OpenShift AI vs Hyperscaler Managed AI: An Honest Verdict (Private AI Series, Part 30)
Three ways to run enterprise inference, three very different trade-offs. A straight comparison of VMware Private AI Foundation, Red Hat OpenShift AI and hyperscaler managed AI, ending in a clear verdict.
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About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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