Take advantage of a 100% OFF coupon code for the 'Ultimate EKS Bootcamp by School of Devops' course, created by Gourav J. Shah , School of Devops, available on Udemy.
This course, updated on September 23, 2025 and it is expired on September 24, 2025.
This course provides 5 hour(s) of expert-led training in English , designed to boost your IT Certifications skills.
Highly rated at 4.5-star stars from 4 reviews, it has already helped 3,314 students.
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Learn Amazon EKS the right way — from fundamentals to advanced autoscaling and monitoring.
This course is designed for DevOps Engineers, Cloud Architects, and Kubernetes practitioners who want to confidently run production workloads on Amazon Elastic Kubernetes Service (EKS).
We’ll start with a practical, lab-driven approach — no endless theory. You’ll begin by setting up your AWS and Kubernetes environment, then progress through deploying workloads, managing networking with ALB ingress, enabling persistent storage, and securing access with IAM Roles for Service Accounts (IRSA).
From there, we’ll tackle scaling strategies — EKS Cluster Autoscaler, Horizontal Pod Autoscaler, Vertical Pod Autoscaler, and advanced solutions like Karpenter for just-in-time node provisioning, and KEDA for event-driven scaling.
Finally, we’ll cover EKS observability with logging, metrics, and dashboards so you can keep your clusters healthy and cost-efficient.
By the end of this bootcamp, you’ll have a production-ready EKS skillset — ready to build, scale, and monitor Kubernetes workloads on AWS.
What You’ll Learn
Set up and configure Amazon EKS clusters from scratch
Deploy applications to EKS using kubectl and manifests
Configure Ingress with AWS ALB Ingress Controller
Attach persistent EBS volumes for stateful workloads
Secure workloads using IAM Roles for Service Accounts (IRSA)
Implement EKS Cluster Autoscaler for node scaling
Apply Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) for workload scaling
Use Karpenter for next-generation cluster scaling
Implement KEDA for event-driven autoscaling scenarios
Monitor and troubleshoot EKS clusters using Prometheus, Grafana, and CloudWatch
Optimize cost and performance for Kubernetes workloads on AWS