• 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

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

Who this course is for:

• DevOps Engineers and Platform Engineers running workloads on AWS
• Kubernetes administrators looking to specialize in AWS EKS
• Cloud Engineers wanting hands-on experience with AWS-native Kubernetes scaling and monitoring
• Anyone preparing for AWS DevOps or Kubernetes certifications with a focus on EKS