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Ultimate EKS Bootcamp by School of Devops
Rating: 4.5 out of 5(22 ratings)
8,183 students
Last updated 8/2025
English

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

Course content

7 sections58 lectures5h 26m total length
  • Module Intro0:47
  • What is EKS ?6:04

    Ultimate EKS Bootcamp - Introduction Module

    Building Your EKS Foundation

    Slide 1: Welcome to the Ultimate EKS Bootcamp

    Master Amazon EKS from Zero to Production

    • Today's Mission:

      • Understand what EKS is and why it matters

      • Learn EKS architecture and core components

      • Explore deployment options and networking

      • Discover real-world use cases and success stories

    Slide 2: What is Amazon EKS?

    The Managed Kubernetes Solution

    Think of EKS as "Kubernetes with Training Wheels":

    • Native Kubernetes: Like building a car from scratch

    • Amazon EKS: Like buying a Tesla - fully featured, maintained, and optimized

    Key Definition:

    • Fully managed Kubernetes service that runs on AWS

    • AWS handles the heavy lifting - control plane, updates, security patches

    • You focus on applications - not infrastructure management

    The Magic Formula:

    EKS = Kubernetes + AWS Integration + Operational Excellence

    Slide 3: EKS vs Native Kubernetes

    Why Choose Managed Over Self-Built?

    Aspect Native Kubernetes Amazon EKS Control Plane You install, manage, upgrade AWS manages completely High Availability You design multi-master setup Built-in across 3 AZs Security Patches Your responsibility AWS handles automatically Upgrades Manual, risky process One-click upgrades Backup/Recovery You implement etcd backups AWS handles it Cost Hidden operational costs Transparent pricing Time to Production Weeks to months Hours to days

    Analogy: Native K8s is like maintaining your own data center, EKS is like using AWS - same power, less hassle!

  • EKS Architecture - Control Plane vs Data Plane6:59

    Slide 4: EKS Architecture - The Big Picture

    Understanding the Two-Tier System

    ┌─────────────────────────────────────────────────────────────┐ │ AWS MANAGED │ │ ┌─────────────────────────────────────────────────────┐ │ │ │ EKS Control Plane │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ │ │ AZ-1 │ │ AZ-2 │ │ AZ-3 │ │ │ │ │ │ API Server │ │ API Server │ │ API Server │ │ │ │ │ │ Scheduler │ │ Scheduler │ │ Scheduler │ │ │ │ │ │ Controller │ │ Controller │ │ Controller │ │ │ │ │ │ etcd │ │ etcd │ │ etcd │ │ │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ └─────────────────────────────────────────────────────┘ │ └─────────────────────────────────────────────────────────────┘ ▲ │ kubectl, APIs ▼ ┌─────────────────────────────────────────────────────────────┐ │ YOUR VPC │ │ ┌─────────────────────────────────────────────────────┐ │ │ │ Data Plane │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ │ │ Node │ │ Node │ │ Fargate │ │ │ │ │ │ Group │ │ Group │ │ Pods │ │ │ │ │ │ (EC2) │ │ (EC2) │ │(Serverless) │ │ │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ └─────────────────────────────────────────────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Key Insight: AWS manages the "brain" (control plane), you control the "muscles" (data plane)

    Slide 5: EKS Control Plane Deep Dive

    What AWS Manages for You

    The Control Plane is like a Restaurant Kitchen:

    • API Server: The head chef taking orders

    • Scheduler: The sous chef assigning dishes to stations

    • Controller Manager: The kitchen manager ensuring everything runs smoothly

    • etcd: The recipe book storing all information

    AWS Magic:

    • Multi-AZ by default - If one kitchen fails, others continue

    • Automatic updates - Latest recipes without downtime

    • Security hardening - Enterprise-grade protection

    • Backup and recovery - Never lose your recipes

    You pay: $0.10/hour per cluster (~$72/month) - that's it!

    Slide 6: Data Plane Options - Where Your Apps Live

    Three Ways to Run Your Workloads

    Option 1: Managed Node Groups

    ┌─────────────────────────────────────┐ │ Auto Scaling Group │ │ ┌─────────┐ ┌─────────┐ ┌─────────┐│ │ │ EC2 │ │ EC2 │ │ EC2 ││ │ │ Instance│ │ Instance│ │ Instance││ │ │ Pod │ │ Pod │ │ Pod ││ │ │ Pod │ │ Pod │ │ Pod ││ │ └─────────┘ └─────────┘ └─────────┘│ └─────────────────────────────────────┘

    Best for: Most workloads, cost-effective, full control

    Option 2: Self-Managed Nodes

    • Complete control over EC2 instances

    • Custom AMIs and configurations

    • More responsibility for updates and patching

    Option 3: AWS Fargate

    ┌─────────────────────────────────────┐ │ Serverless │ │ ┌─────────┐ ┌─────────┐ ┌─────────┐│ │ │ Pod │ │ Pod │ │ Pod ││ │ │ (Right │ │ (Right │ │ (Right ││ │ │ Size) │ │ Size) │ │ Size) ││ │ └─────────┘ └─────────┘ └─────────┘│ └─────────────────────────────────────┘

    Best for: Variable workloads, no server management

    Slide 7: Node Groups vs Fargate - The Decision Matrix

    When to Use What?

    Use Case Managed Node Groups AWS Fargate Steady workloads ✅ Cost-effective ❌ More expensive Variable workloads ❌ Always running ✅ Pay per use Custom requirements ✅ Full control ❌ Limited options Operational overhead ⚠️ Some management ✅ Zero management Startup time ✅ Fast ⚠️ Slower cold start Debugging ✅ SSH access ❌ No node access

    Pro Tip: Start with managed node groups, add Fargate for specific use cases!

    Real-world example: Use node groups for web servers, Fargate for batch jobs

  • EKS Networking with VPC CNI, Setup Options and Add-ons7:33

    Slide 8: EKS Networking - The Connectivity Story

    How Everything Talks to Everything

    VPC Native Networking

    ┌─────────────────────────────────────────────────────────────┐ │ VPC │ │ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────┐ │ │ │ Subnet A │ │ Subnet B │ │ Subnet C │ │ │ │ (AZ-1) │ │ (AZ-2) │ │ (AZ-3) │ │ │ │ ┌─────────────┐ │ │ ┌─────────────┐ │ │┌─────────────┐│ │ │ │ │Pod: 10.0.1.5│ │ │ │Pod:10.0.2.10│ │ ││Pod:10.0.3.15││ │ │ │ │Pod: 10.0.1.6│ │ │ │Pod:10.0.2.11│ │ ││Pod:10.0.3.16││ │ │ │ └─────────────┘ │ │ └─────────────┘ │ │└─────────────┘│ │ │ └─────────────────┘ └─────────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Key Concepts:

    • Each pod gets a real VPC IP - no NAT needed!

    • AWS VPC CNI - Native AWS networking

    • Security Groups apply to pods directly

    • Network ACLs provide subnet-level security

    Coming in Labs: We'll configure ALB ingress and EBS storage networking

    Slide 9: EKS Setup Options - Choose Your Adventure

    Multiple Paths to Success

    1. eksctl - The Easy Button

    # One command to rule them all eksctl create cluster --name my-cluster --region us-west-2

    Best for: Quick start, learning, development

    2. AWS CLI + kubectl - The Manual Way

    # Step by step control aws eks create-cluster --name my-cluster... aws eks create-nodegroup --cluster-name my-cluster...

    Best for: Understanding internals, custom configurations

    3. Terraform - The Infrastructure as Code Way

    resource "aws_eks_cluster" "main" { name = "my-cluster" role_arn = aws_iam_role.cluster.arn # ... more configuration }

    Best for: Production environments, repeatable deployments

    4. AWS CDK - The Developer-Friendly Way

    new eks.Cluster(this, 'MyCluster', { version: eks.KubernetesVersion.V1_27, });

    In Our Labs: We'll start with eksctl, then explore AWS CLI methods

    Slide 10: EKS Add-ons - Supercharging Your Cluster

    The Plugin Ecosystem

    Core Add-ons (Essential)

    ┌─────────────────────────────────────────────────────────────┐ │ EKS Cluster │ │ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────┐ │ │ │ AWS Load │ │ Amazon EBS │ │ CoreDNS │ │ │ │ Balancer │ │ CSI Driver │ │ (DNS) │ │ │ │ Controller │ │ (Storage) │ │ │ │ │ └─────────────────┘ └─────────────────┘ └─────────────┘ │ │ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────┐ │ │ │ VPC CNI │ │ kube-proxy │ │ Amazon │ │ │ │ (Networking) │ │ (Networking) │ │ GuardDuty │ │ │ │ │ │ │ │ (Security) │ │ │ └─────────────────┘ └─────────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Popular Third-Party Add-ons

    • Monitoring: Prometheus, Grafana, Loki

    • Security: Falco, Twistlock

    • Networking: Istio, Linkerd

    • Storage: EFS CSI, FSx CSI

    In Our Labs: We'll install and configure ALB Controller, EBS CSI Driver, and monitoring stack

  • Real World Use Cases - Netflix, Snapchat and more5:44

    Slide 11: Real-World EKS Success Stories

    Who's Using EKS and Why

    ? Spotify

    • Challenge: Scale music streaming for 500M+ users

    • Solution: EKS for microservices architecture

    • Result: 40% reduction in infrastructure costs

    ? Netflix

    • Challenge: Global content delivery platform

    • Solution: EKS for data processing and ML pipelines

    • Result: Faster feature deployment, better reliability

    ? Snapchat

    • Challenge: Handle billions of daily messages

    • Solution: EKS with Fargate for variable workloads

    • Result: 60% cost savings on compute resources

    ? Capital One

    • Challenge: Modernize banking infrastructure

    • Solution: EKS for cloud-native transformation

    • Result: Faster innovation, improved security

    ? Shopify

    • Challenge: Handle Black Friday traffic spikes

    • Solution: EKS with cluster autoscaling

    • Result: Seamless scaling from 1K to 100K+ requests/sec


  • EKS Usage Patterns, Storage, Security, Autoscaling, Observability10:38

    Slide 12: EKS in Your Architecture

    Common Patterns and Use Cases

    Pattern 1: Microservices Architecture

    ┌─────────────────────────────────────────────────────────────┐ │ Application Layer │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ User │ │ Product │ │ Order │ │ │ │ Service │ │ Service │ │ Service │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ User │ │ Product │ │ Order │ │ │ │ Database │ │ Database │ │ Database │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Pattern 2: Data Processing Pipeline

    Data Ingestion → EKS Processing → Analytics → Visualization ↓ ↓ ↓ ↓ Kinesis → Spark Jobs → S3 → QuickSight

    Pattern 3: CI/CD Platform

    Code Push → Build (EKS) → Test (EKS) → Deploy (EKS) → Monitor

    Slide 13: EKS Networking Deep Dive

    Understanding the Network Flow

    Pod-to-Pod Communication

    ┌─────────────────────────────────────────────────────────────┐ │ Same Node │ │ ┌─────────────┐ ┌─────────────┐ │ │ │ Pod A │ ────────→ │ Pod B │ │ │ │ 10.0.1.100 │ │ 10.0.1.101 │ │ │ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘ ┌─────────────────────────────────────────────────────────────┐ │ Different Nodes │ │ ┌─────────────┐ ┌─────────────┐ │ │ │ Pod A │ ────────→ │ Pod C │ │ │ │ 10.0.1.100 │ VPC │ 10.0.2.100 │ │ │ │ Node 1 │ Routing │ Node 2 │ │ │ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Service Types We'll Use

    • ClusterIP: Internal communication only

    • NodePort: Access via node IP and port

    • LoadBalancer: AWS ELB integration

    • Ingress: HTTP/HTTPS routing (ALB)

    Lab Preview: We'll configure ALB ingress for our microservices app

    Slide 14: Storage in EKS - Persistent Data Solutions

    Where Your Data Lives

    Storage Options

    ┌─────────────────────────────────────────────────────────────┐ │ EKS Storage │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ EBS │ │ EFS │ │ FSx │ │ │ │ (Block │ │ (Network │ │ (High │ │ │ │ Storage) │ │ File) │ │ Performance)│ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ Databases │ │ Shared │ │ HPC │ │ │ │ StatefulSets│ │ Storage │ │ Workloads │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Container Storage Interface (CSI)

    • EBS CSI Driver - Block storage for databases

    • EFS CSI Driver - Shared file storage

    • FSx CSI Driver - High-performance workloads

    In Our Labs: We'll configure EBS storage for a database and set up persistent volumes

    Slide 15: Security in EKS - Defense in Depth

    Multiple Layers of Protection

    Identity and Access Management

    ┌─────────────────────────────────────────────────────────────┐ │ Security Layers │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ IAM │ │ RBAC │ │ IRSA │ │ │ │ (AWS │ │ (Kubernetes │ │ (Pod-level │ │ │ │ Level) │ │ Level) │ │ AWS) │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ Cluster │ │ Namespace │ │ Pod │ │ │ │ Access │ │ Access │ │ Access │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Network Security

    • Security Groups - Instance-level firewall

    • Network ACLs - Subnet-level firewall

    • Network Policies - Pod-to-pod communication rules

    Lab Highlight: We'll implement IRSA to give pods secure access to S3 buckets

    Slide 16: Autoscaling in EKS - Scale with Demand

    Three Dimensions of Scaling

    Horizontal Pod Autoscaler (HPA)

    Low Traffic: [Pod] [Pod] High Traffic: [Pod] [Pod] [Pod] [Pod] [Pod]

    Vertical Pod Autoscaler (VPA)

    Low Load: [Pod: 1 CPU, 1GB RAM] High Load: [Pod: 2 CPU, 4GB RAM]

    Cluster Autoscaler

    Light Usage: [Node] [Node] Heavy Usage: [Node] [Node] [Node] [Node]

    Advanced Topics Coming:

    • KEDA - Event-driven autoscaling

    • Karpenter - Next-gen node provisioning

    In Our Labs: We'll configure all three autoscaling methods with real workloads

    Slide 17: Monitoring and Observability

    See Everything, Understand Everything

    The Three Pillars

    ┌─────────────────────────────────────────────────────────────┐ │ Observability │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ Metrics │ │ Logs │ │ Traces │ │ │ │ (Prometheus)│ │ (Loki) │ │ (Jaeger) │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ Grafana │ │ CloudWatch │ │ X-Ray │ │ │ │(Dashboards) │ │ (AWS Native)│ │(AWS Tracing)│ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Monitoring Stack Options

    • AWS Native: CloudWatch + Container Insights

    • Open Source: Prometheus + Grafana + Loki

    • Hybrid: Best of both worlds

    Lab Preview: We'll set up comprehensive monitoring with both approaches

  • Your Learning Journey, Lab Environment, Success Metrics8:40

    Slide 12: EKS in Your Architecture

    Common Patterns and Use Cases

    Pattern 1: Microservices Architecture

    ┌─────────────────────────────────────────────────────────────┐ │ Application Layer │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ User │ │ Product │ │ Order │ │ │ │ Service │ │ Service │ │ Service │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ User │ │ Product │ │ Order │ │ │ │ Database │ │ Database │ │ Database │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Pattern 2: Data Processing Pipeline

    Data Ingestion → EKS Processing → Analytics → Visualization ↓ ↓ ↓ ↓ Kinesis → Spark Jobs → S3 → QuickSight

    Pattern 3: CI/CD Platform

    Code Push → Build (EKS) → Test (EKS) → Deploy (EKS) → Monitor

    Slide 13: EKS Networking Deep Dive

    Understanding the Network Flow

    Pod-to-Pod Communication

    ┌─────────────────────────────────────────────────────────────┐ │ Same Node │ │ ┌─────────────┐ ┌─────────────┐ │ │ │ Pod A │ ────────→ │ Pod B │ │ │ │ 10.0.1.100 │ │ 10.0.1.101 │ │ │ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘ ┌─────────────────────────────────────────────────────────────┐ │ Different Nodes │ │ ┌─────────────┐ ┌─────────────┐ │ │ │ Pod A │ ────────→ │ Pod C │ │ │ │ 10.0.1.100 │ VPC │ 10.0.2.100 │ │ │ │ Node 1 │ Routing │ Node 2 │ │ │ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Service Types We'll Use

    • ClusterIP: Internal communication only

    • NodePort: Access via node IP and port

    • LoadBalancer: AWS ELB integration

    • Ingress: HTTP/HTTPS routing (ALB)

    Lab Preview: We'll configure ALB ingress for our microservices app

    Slide 14: Storage in EKS - Persistent Data Solutions

    Where Your Data Lives

    Storage Options

    ┌─────────────────────────────────────────────────────────────┐ │ EKS Storage │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ EBS │ │ EFS │ │ FSx │ │ │ │ (Block │ │ (Network │ │ (High │ │ │ │ Storage) │ │ File) │ │ Performance)│ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ Databases │ │ Shared │ │ HPC │ │ │ │ StatefulSets│ │ Storage │ │ Workloads │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Container Storage Interface (CSI)

    • EBS CSI Driver - Block storage for databases

    • EFS CSI Driver - Shared file storage

    • FSx CSI Driver - High-performance workloads

    In Our Labs: We'll configure EBS storage for a database and set up persistent volumes

    Slide 15: Security in EKS - Defense in Depth

    Multiple Layers of Protection

    Identity and Access Management

    ┌─────────────────────────────────────────────────────────────┐ │ Security Layers │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ IAM │ │ RBAC │ │ IRSA │ │ │ │ (AWS │ │ (Kubernetes │ │ (Pod-level │ │ │ │ Level) │ │ Level) │ │ AWS) │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ Cluster │ │ Namespace │ │ Pod │ │ │ │ Access │ │ Access │ │ Access │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Network Security

    • Security Groups - Instance-level firewall

    • Network ACLs - Subnet-level firewall

    • Network Policies - Pod-to-pod communication rules

    Lab Highlight: We'll implement IRSA to give pods secure access to S3 buckets

    Slide 16: Autoscaling in EKS - Scale with Demand

    Three Dimensions of Scaling

    Horizontal Pod Autoscaler (HPA)

    Low Traffic: [Pod] [Pod] High Traffic: [Pod] [Pod] [Pod] [Pod] [Pod]

    Vertical Pod Autoscaler (VPA)

    Low Load: [Pod: 1 CPU, 1GB RAM] High Load: [Pod: 2 CPU, 4GB RAM]

    Cluster Autoscaler

    Light Usage: [Node] [Node] Heavy Usage: [Node] [Node] [Node] [Node]

    Advanced Topics Coming:

    • KEDA - Event-driven autoscaling

    • Karpenter - Next-gen node provisioning

    In Our Labs: We'll configure all three autoscaling methods with real workloads

    Slide 17: Monitoring and Observability

    See Everything, Understand Everything

    The Three Pillars

    ┌─────────────────────────────────────────────────────────────┐ │ Observability │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ Metrics │ │ Logs │ │ Traces │ │ │ │ (Prometheus)│ │ (Loki) │ │ (Jaeger) │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ Grafana │ │ CloudWatch │ │ X-Ray │ │ │ │(Dashboards) │ │ (AWS Native)│ │(AWS Tracing)│ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────────┘

    Monitoring Stack Options

    • AWS Native: CloudWatch + Container Insights

    • Open Source: Prometheus + Grafana + Loki

    • Hybrid: Best of both worlds

    Lab Preview: We'll set up comprehensive monitoring with both approaches

  • Summary1:01

    Slide 22: Additional Resources

    Continue Your Learning

    Official Documentation

    • AWS EKS User Guide: https://docs.aws.amazon.com/eks/

    • Kubernetes Documentation: https://kubernetes.io/docs/

    • eksctl Documentation: https://eksctl.io/

    Recommended Reading

    • "Kubernetes in Action" by Marko Lukša

    • "AWS Certified Solutions Architect" by Neil Davis

    • AWS Well-Architected Framework: Container workloads

    Community Resources

    • AWS EKS GitHub: https://github.com/aws/amazon-eks-pod-identity-webhook

    • Kubernetes Slack: #eks-users channel

    • AWS re:Invent Sessions: EKS-focused talks

    Practice Environments

    • AWS Free Tier: Limited EKS usage

    • Kubernetes Playground: https://labs.play-with-k8s.com/

    • Local Development: minikube, kind, k3s


Requirements

  • Basic understanding of Kubernetes concepts (pods, deployments, services)
  • AWS account with administrative access
  • Familiarity with basic AWS services like EC2, IAM, and VPC
  • Command-line experience (bash or similar)

Description

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