File Name: | AI ML GenAI on NVIDIA H100 GPUs on Red Hat OpenShift AI |
Content Source: | https://www.udemy.com/course/deploying-nvidia-gpus-on-red-hat-openshift-ai |
Genre / Category: | Other Tutorials |
File Size : | 817.1 MB |
Publisher: | Luca Berton |
Updated and Published: | July 27, 2025 |
Unlock the power of enterprise-grade AI in your own data center—step-by-step, from bare-metal to production-ready inference. In this hands-on workshop, you’ll learn how to transform a single NVIDIA H100 server and a lightweight virtualization host into a fully featured Red Hat OpenShift cluster running OpenShift AI, the NVIDIA GPU Operator, and real LLM workloads (Mistral-7B with Ollama). We skip the theory slides and dive straight into keyboards and terminals—every YAML, every BIOS toggle, every troubleshooting trick captured on video.
What you’ll build:
- A three-node virtual control plane + one bare-metal GPU worker, deployed via the new Agent-based Installer
- GPU Operator with MIG slicing, UUID persistence, and live metrics in Grafana
- OpenShift AI (RHODS) with Jupyter and model-serving pipelines
- A production-grade load balancer, DNS zone, and HTTPS ingress—no managed cloud needed
Hands-on every step: you’ll inspect firmware through iDRAC, patch BIOS settings, generate a custom Agent ISO, boot the cluster, join the GPU node, and push an LLM endpoint you can curl in under a minute. Along the way, we’ll upgrade OpenShift, monitor GPU temps, and rescue a “Node Not Ready” scenario—because real life happens.
Who should enroll
DevOps engineers, SREs, and ML practitioners who have access to a GPU server (H100, H800, or even an A100) and want a repeatable, enterprise-compatible install path. Basic Linux and kubectl skills are assumed; everything else is taught live.
By course end, you’ll have a battle-tested Git repository full of manifests, a private Agent ISO pipeline you can clone for new edge sites, and the confidence to stand up—or scale out—your own GPU-accelerated OpenShift AI platform. Join us and ship your first on-prem LLM workload today.
Who this course is for:
- Machine Learning Engineers
- DevOps Engineers
- Site Reliability Engineers (SREs)
- Python Developers Exploring Infrastructure
- First Steppers into AI Operations
DOWNLOAD LINK: AI ML GenAI on NVIDIA H100 GPUs on Red Hat OpenShift AI
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