Red Hat OpenShift AI
Enterprise AI/ML platform on Kubernetes for the full model lifecycle: training, serving and management.
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What is this technology for?
Its role in production environments and why it is taught in our curriculums.
Red Hat OpenShift AI (RHOAI) is the enterprise AI/ML platform on Kubernetes covering the full model lifecycle — notebooks, training, serving and monitoring — with consistent GitOps and RBAC.
What you will learn
The hands-on skills you will gain on this technology in our curriculums.
- Deploy RHOAI on an existing OpenShift cluster
- Configure model serving infrastructure for LLM inference
- Build and run MLOps/LLMOps pipelines
- Manage quotas, GPU pools and model versioning for production
Latest News & Ecosystem Updates
Recent innovations, major releases, and key industry milestones in the ecosystem.
Red Hat OpenShift AI 2.18: Full Multi-Agent Architecture Support
End-to-end enterprise platform to orchestrate autonomous agentic swarms with built-in governance and observability.
Native vLLM & KServe Integration for High-Throughput Inference
3x throughput gain on enterprise LLM requests leveraging dynamic continuous token batching (PagedAttention).
Featured in the curriculum
Find this technology in the following modules of our Red Hat certified curriculums.
AS300 — AI Platform Engineer
View curriculum →
Red Hat OpenShift AI (RHOAI)
AI267 · Module 7 — AS300
GenAI Fundamentals + Granite + RHEL AI
AI296 · Module 8 — AS300
