📌 Key Takeaways

  • Amazon EKS is the most widely adopted managed Kubernetes platform in production.
  • AWS charges a flat rate of $0.10/hour per cluster control plane, managed across 3 availability zones.
  • IRSA (IAM Roles for Service Accounts) is the cloud-native standard for securing AWS service access.
  • Karpenter and Cluster Autoscaler optimize scaling of EC2 worker nodes automatically.
  • Thick Brain Technology provides hands-on Advanced Kubernetes training with dedicated EKS cluster labs.

Amazon Elastic Kubernetes Service (EKS) has emerged as the industry standard for running production Kubernetes workloads on AWS. Highly integrated with AWS security, networking, and storage, EKS removes the operational complexity of managing the master control plane, letting DevOps teams focus on application deployment. This guide explores Amazon EKS architecture, node management strategies, security, and troubleshooting.

What is Amazon EKS?

Amazon EKS is a managed service that makes it easy to run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane. It is certified Kubernetes conformant, meaning existing applications running on standard Kubernetes are fully compatible with EKS.

AWS handles control plane management, including automated scaling, upgrades, and multi-AZ deployment for high availability. EKS automatically runs the Kubernetes API server and etcd across multiple Availability Zones, ensuring cluster resilience and zero control plane downtime.

Amazon EKS Architecture

An EKS cluster consists of two main parts: the AWS-managed control plane and the customer-provisioned worker nodes running in your own VPC.

1. The Control Plane

AWS deploys the Kubernetes control plane in a dedicated AWS-managed VPC. It consists of at least three API servers and three etcd nodes distributed across three Availability Zones. This setup is managed via AWS-managed load balancers to distribute traffic to the API servers.

2. The Worker Nodes

Worker nodes run in your own VPC and connect back to the managed control plane. You have three choices for worker node compute in EKS:

  • Managed Node Groups — Automated EC2 instances where AWS manages VM provisioning, upgrades, and drain/evict actions during node lifecycle.
  • Self-Managed Nodes — Custom EC2 instances configured and connected manually, offering maximum VM-level control.
  • AWS Fargate — Serverless compute option where pods are run in secure isolated environments, billing only for resources used per-pod.

Managed Node Groups vs Self-Managed Nodes

For most enterprises, Managed Node Groups are the preferred way to run worker nodes. Under this setup, AWS manages the provisioning and lifecycle of the underlying EC2 instances. When you upgrade your EKS cluster version, AWS handles updating the worker nodes by deploying new nodes with the updated AMI, draining the old nodes cleanly, and terminating them.

Self-managed nodes are still used for custom operating system configurations, complex bootstrap scripts, or niche hardware requirements (such as specific GPU workloads or custom kernels).

EKS Fargate (Serverless Kubernetes)

AWS Fargate allows you to run Kubernetes pods without having to manage EC2 instances or node pools. You define a Fargate profile specifying which namespaces and labels should run on Fargate. When a matching pod is scheduled, EKS automatically provisions a lightweight virtual machine specifically for that pod.

While Fargate simplifies capacity planning and increases security through isolation, it has some limitations: DaemonSets are not supported, privileged containers are disabled, and pods cannot mount EBS volumes directly (though EFS is supported).

IAM Roles for Service Accounts (IRSA)

Security is a key aspect of EKS. In traditional EC2 clusters, pods assumed the IAM role attached to the worker node's EC2 instance profile, violating the principle of least privilege. EKS introduced IRSA, which uses OpenID Connect (OIDC) federation.

With IRSA, you associate an IAM role directly with a Kubernetes ServiceAccount. The Amazon EKS Pod Identity Webhook intercepts pod creation, injecting AWS environment variables and token credentials into the container. The pod can then call AWS services (such as S3, DynamoDB, or KMS) securely, using permissions scoped specifically to that pod.

Cluster Setup with eksctl

The eksctl CLI is the official command-line tool for Amazon EKS, developed in collaboration with Weaveworks. It allows you to provision an entire cluster in a single command, automating VPC creation, security groups, subnets, and node groups:

eksctl create cluster --name tbt-prod --version 1.28 --nodegroup-name standard-workers --node-type t3.medium --nodes 3 --nodes-min 1 --nodes-max 5 --region ap-south-1

This command automates the generation of CloudFormation templates and configures your local kubeconfig so you can run kubectl commands immediately.

EKS Scaling: Cluster Autoscaler & Karpenter

To scale worker nodes in EKS, two methods are common:

  • Cluster Autoscaler — Watches for unschedulable pods due to resource constraints and adjusts AWS Auto Scaling Group (ASG) capacity.
  • Karpenter — A high-performance Kubernetes node provisioner built by AWS. Karpenter bypasses Auto Scaling Groups, calling EC2 Fleet APIs directly to launch optimal instances based on pod specifications in under a minute, improving resource utilization and startup speed.

Monitoring EKS with CloudWatch & Container Insights

Monitoring EKS involves collecting control plane logs (API server, audit logs) and worker node metrics. By enabling CloudWatch Container Insights, AWS deploys a CloudWatch agent DaemonSet that automatically collects container metrics (CPU, memory, network, disk) and pushes them to CloudWatch Dashboards, giving full visibility into application performance.

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AWS EKS Interview Questions & Answers

Prepare for your next AWS DevOps interview with these EKS-specific questions. For general Kubernetes questions, refer to our Core Kubernetes Guide.

Showing 10 questions
Amazon Elastic Kubernetes Service (EKS) is a managed Kubernetes service on AWS. EKS runs the control plane (API server, etcd, scheduler) across multiple AZs for high availability. The control plane is managed by AWS — you pay $0.10/hour. The worker nodes run in your AWS account (EC2). EKS integrates with IAM, VPC, CloudWatch, and ALB (via AWS Load Balancer Controller). EKS is the most popular managed Kubernetes in production.
eksctl is the official CLI for EKS. Install: brew install eksctl. Create a cluster: eksctl create cluster --name=prod --version=1.28 --nodegroup-name=standard-workers --node-type=t3.medium --nodes=3 --nodes-min=1 --nodes-max=5 --region=ap-south-1. This creates the control plane, worker nodes, and configures kubectl automatically. EKSCTL is the fastest way to create an EKS cluster for development and production.
The AWS Load Balancer Controller is a Kubernetes controller that manages AWS load balancers (ALB, NLB) based on Ingress and Service resources. It watches for Ingress resources with kubernetes.io/ingress.class: alb and automatically provisions an Application Load Balancer (ALB) and configures routing. Benefits: (1) Integration with ACM for TLS. (2) Path-based routing. (3) Sticky sessions. (4) WAF integration. Standard EKS setup includes this controller.
Managed node groups — AWS handles the lifecycle of EC2 nodes (creation, scaling, termination, AMI updates). You specify instance type and size; AWS manages the rest. Self-managed nodes — you create and manage EC2 instances, install Kubernetes, and join them to the cluster. Use managed node groups for most workloads (less operational overhead). Use self-managed nodes for: (1) Custom AMIs. (2) Special instance types (GPU). (3) Bin packing optimisations.
EKS Fargate is a serverless compute engine for Kubernetes — you define pods, AWS runs them on Fargate without managing any nodes. Benefits: (1) No node management. (2) Pay per pod (not per node). (3) Automatic scaling. Limitations: (1) No DaemonSets. (2) No privileged containers. (3) Pods only (no node-level access). Use Fargate for serverless workloads, batch jobs, and teams that want to avoid node management. Use EC2 for high-performance or stateful workloads.
IRSA allows Kubernetes ServiceAccounts to assume IAM roles. Steps: (1) Create an IAM role with a trust policy that allows the EKS cluster's OIDC provider to assume the role. (2) Annotate the ServiceAccount with the IAM role ARN. (3) The pod uses the ServiceAccount, and the Kubernetes webhook automatically injects the AWS credentials into the pod. Benefits: (1) No static AWS keys. (2) Fine-grained IAM permissions per pod. (3) Security best practice. IRSA is the standard way to access AWS services from EKS.
The EKS cluster autoscaler scales the number of worker nodes based on pod resource demands. It watches for unschedulable pods (due to insufficient node capacity) and adds nodes. It also removes idle nodes. Configuration: set the cluster-autoscaler deployment with the correct AWS region, auto-scaling group names, and scale-up/down policies. Best practice: enable cluster autoscaler for all production EKS clusters to handle workload spikes automatically.
Two approaches: (1) EKS control plane logging — enable logs for API server, scheduler, controller manager, audit logs, and authenticator in the EKS console. (2) CloudWatch Container Insights — automatically collects metrics (CPU, memory, network) and logs from pods and nodes. To enable: kubectl apply -f https://raw.githubusercontent.com/aws-samples/amazon-cloudwatch-container-insights/latest/k8s-deployment-manifest-templates/deployment-mode/daemonset/container-insights-monitoring/quickstart/cwagent-fluentd-quickstart.yaml.
EKS is managed Kubernetes — you get the full Kubernetes API, ecosystem (Helm, ArgoCD, Prometheus), and portability across clouds. ECS is AWS's native container orchestrator — simpler to set up and use, with deep AWS integration (CloudWatch, Service Discovery, IAM). Use EKS for: (1) Multi-cloud or hybrid deployments. (2) Kubernetes-specific tooling. (3) Complex workloads. Use ECS for: (1) AWS-only deployments. (2) Simpler needs. (3) Cost sensitivity (ECS control plane is free).
EKS security best practices: (1) Enable RBAC — use AWS IAM for authentication, map to Kubernetes RBAC. (2) Use IRSA — no static keys. (3) NetworkPolicy — use Calico or Cilium. (4) Encrypt etcd — enable encryption provider for secrets. (5) Enable control plane logging — audit logs, API server logs. (6) Use security groups — restrict node group communication. (7) Run kube-bench — monthly compliance scans. (8) Enable Pod Security Admission (PSA) — enforce pod security standards.

Frequently Asked Questions

Amazon Elastic Kubernetes Service (EKS) is a managed Kubernetes service on AWS. It handles master node management, replication, and high availability of control plane nodes, allowing you to run standard Kubernetes apps seamlessly.
AWS charges a flat rate of $0.10/hour (approx. $73/month) per EKS cluster control plane. You also pay standard rates for worker node instances (EC2), load balancers, and persistent storage (EBS/EFS) that you provision.
EKS integrates with AWS IAM for authentication (using AWS IAM Authenticator) and pod-level permissions (via IAM Roles for Service Accounts - IRSA). This maps AWS IAM roles directly to Kubernetes ServiceAccounts.
Karpenter is an open-source Kubernetes node auto-provisioner built by AWS. It improves application availability and cluster efficiency by directly provisioning optimal EC2 instances in response to pending pods, starting new instances in seconds.

Conclusion: Master Amazon EKS

Amazon EKS has become the standard for running containers in the enterprise. Building skills in AWS-managed Kubernetes, IRSA, eksctl, and CloudWatch makes you highly competitive in the DevOps job market.

Thick Brain Technology offers advanced Kubernetes training focusing heavily on AWS EKS, providing real cluster labs where you deploy, secure, and scale production-ready applications. Book a free demo class to start practicing on live EKS clusters.