OpenShift Enterprise Cluster Masterclass: Deploy, Scale, Run

About this course

Master Red Hat OpenShift 4 Infrastructure, AWS Integration, and Enterprise AI Scaling!Are you ready to build, manage, and scale production-grade OpenShift clusters on AWS? Welcome to the ultimate hands-on guide designed for Cloud Engineers, DevOps Professionals, and MLOps Specialists. This course takes you step-by-step through deploying OpenShift 4 using the User Provisioned Infrastructure (UPI) method—giving you total control over your enterprise cloud environment.From day one, you will get your hands dirty with real-world cloud architecture. You will learn how to configure an AWS EC2 Bastion host, set up IAM programmatic access, and automate domain delegation using AWS Route 53 and GoDaddy DNS. Moving into cluster deployment, we dive deep into customizing install-config.yaml manifests, establishing high-availability (HA) control planes, and avoiding critical AWS vCPU quota limit pitfalls.Once your cluster is live, you’ll master daily cluster administration using both the OpenShift Web Console and the oc CLI. You will inspect nodes, debug CRI-O container runtime health, analyze resource allocations (millicores and memory), and demystify core platform concepts like Projects, Routes, and MachineSets.Finally, we unlock advanced AI/ML infrastructure engineering. You will learn how to scale worker nodes dynamically using MachineSets and MachineAutoscalers, handle real NVIDIA GPU instance types (G4dn series), and deploy Helm charts. Plus, you’ll discover how to leverage K-Work (KWOAK) to simulate virtual GPU nodes for zero-cost AI and LLM inference testing before spending a dime in production!What Makes This Course Unique?100% Hands-On & Practical: No fluff—just real terminal commands, custom YAML configurations, and active AWS deployments.Production-Ready UPI Method: Learn the exact deployment s

Course objectives

• provide practical experience in launching OpenShift clusters
• develop skills in cloud architecture and administration
• prepare for advanced AI/ML infrastructure challenges