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A Practical Guide to AWS EKS: Deploying Kubernetes on AWS

A Practical Guide to AWS EKS: Deploying Kubernetes on AWS

Managing Kubernetes clusters can be complex, especially when you balance reliability, security, and cost. Amazon Web Services provides a managed Kubernetes service called AWS EKS (Elastic Kubernetes Service) to simplify cluster operations while giving you the flexibility to run containerized workloads at scale. In this guide, you will find a practical, hands-on walkthrough that mirrors a typical AWS EKS tutorial. The goal is to help you understand the core concepts, set up a cluster, deploy an application, and observe how EKS integrates with AWS services to deliver a robust Kubernetes experience.

What is AWS EKS?

AWS EKS is a managed control plane for Kubernetes that runs and scales the Kubernetes API server in a highly available configuration. With EKS, you don’t have to provision or manage the Kubernetes master nodes yourself. AWS handles control plane security, patching, and high availability across multiple AZs, while you focus on your workloads. The worker nodes can be managed by AWS or brought in as your own EC2 instances, and you can also use AWS Fargate to run pods without managing servers. In short, AWS EKS provides a ready-made, secure, and scalable foundation for Kubernetes workloads on AWS.

Prerequisites

  • An AWS account with appropriate permissions to create EKS resources, IAM roles, VPCs, and EC2 instances.
  • The AWS CLI installed and configured with a default region.
  • eksctl installed for quick cluster provisioning, and kubectl installed to interact with the cluster.
  • Basic familiarity with Kubernetes concepts (pods, deployments, services, and namespaces).

Having these prerequisites in place makes the AWS EKS workflow smoother. If you’re new to Kubernetes, consider taking a quick refresher on kubectl commands and a simple deployment before diving into EKS specifics.

Step-by-step: Create an EKS cluster with eksctl

The fastest way to stand up an EKS cluster is to use eksctl, a command-line tool designed to simplify cluster creation. The following steps outline a typical workflow for creating a small, production-like cluster.

  1. Ensure your AWS CLI is configured with a profile that has permissions to create EKS resources.
  2. Verify your IAM user has the necessary permissions for EKS, EC2, IAM Roles for Service Accounts (IRSA), and VPC resources.
  3. Prepare a VPC or use the default VPC with subnets across at least two AZs for high availability.
  4. Run the cluster creation command with a sensible node group configuration:
eksctl create cluster \
  --name my-eks-cluster \
  --region us-west-2 \
  --nodegroup-name standard-workers \
  --node-type t3.medium \
  --nodes 3 \
  --nodes-min 1 \
  --nodes-max 4 \
  --managed

This command tells eksctl to provision a managed node group in the chosen region and to spin up three worker nodes by default. The managed node group makes it easier to apply updates and manage lifecycle events. After a few minutes, the cluster control plane is created and ready to use. Next, configure your local kubectl to talk to the new cluster.

aws eks --region us-west-2 update-kubeconfig --name my-eks-cluster

Running the update-kubeconfig command creates or updates the kubeconfig file so that kubectl can authenticate with the EKS cluster control plane. You can verify the cluster context with:

kubectl config current-context

At this point, you should see your EKS cluster as the current context. You’re ready to deploy workloads.

Deploy a simple application

One of the easiest ways to validate your EKS setup is to deploy a small web application. Here is a minimal Deployment manifest for an NGINX server, followed by a Service to expose it.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nginx-deployment
  labels:
    app: nginx
spec:
  replicas: 2
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx:1.23
        ports:
        - containerPort: 80

apiVersion: v1
kind: Service
metadata:
  name: nginx-service
spec:
  type: LoadBalancer
  selector:
    app: nginx
  ports:
  - port: 80
    targetPort: 80

Apply these manifests to your cluster:

kubectl apply -f nginx-deployment.yaml
kubectl apply -f nginx-service.yaml

You should eventually see a LoadBalancer being provisioned in AWS. This Load Balancer will route external traffic to your NGINX pods, providing a simple, real-world test of your EKS cluster’s networking and security configuration. Monitor the rollout with:

kubectl rollout status deployment/nginx-deployment

As long as the pods are healthy, the service will be reachable via the external IP address assigned by the Load Balancer. This basic workflow demonstrates how AWS EKS can host containerized workloads with minimal manual intervention.

Leveraging AWS features with EKS

AWS EKS shines when you integrate Kubernetes with AWS-native services. Consider these enhancements:

  • Use IAM Roles for Service Accounts (IRSA) to securely grant pods access to AWS resources without static credentials. This tightens security and aligns with least-privilege principles.
  • Enable the Kubernetes Cluster Autoscaler to adjust the number of nodes in response to workload changes, optimizing cost and performance.
  • Run stateful workloads with EBS-backed storage or S3-compatible storage, using StatefulSets and PersistentVolumeClaims for data durability.
  • Leverage AWS Load Balancer Controller to provision and manage Application Load Balancers (ALBs) and Network Load Balancers (NLBs) for Kubernetes services.
  • Explore AWS Fargate for serverless compute, running pods without managing individual EC2 instances.

These features help you balance performance, security, and cost while keeping your Kubernetes workflow aligned with AWS best practices. When you start introducing more complex services, AWS EKS remains a solid base for a production-grade cluster.

Observability, security, and governance

Observability is essential for diagnosing issues and maintaining uptime. In AWS EKS, you can enable and centralize logs from the Kubernetes control plane and worker nodes into CloudWatch. For application-level metrics, consider integrating Prometheus and Grafana within the cluster or using AWS Managed Service for Prometheus. Logging, tracing, and dashboards are key to discovering issues before end users are affected.

Security considerations include network segmentation with VPCs, security groups, and private subnets, as well as role-based access control (RBAC) within Kubernetes. Regularly review IAM roles and policies used by your cluster, and prefer using IRSA for AWS integrations rather than long-lived credentials. Keeping the EKS control plane updated with AWS security patches and enabling automatic upgrades helps minimize vulnerabilities.

Operational tips and best practices

  • Start with a minimal, production-like configuration and scale up as needed. This helps manage cost and complexity.
  • Use namespaces to isolate environments (development, staging, production) and apply resource quotas to prevent noisy neighbors.
  • Adopt a GitOps workflow: store Kubernetes manifests in version control and automate deployments with tools like ArgoCD or Flux.
  • Regularly back up critical data, especially for stateful workloads and databases, using reliable storage classes and snapshot mechanisms.
  • Test failover and disaster recovery, including node failures and AZ outages, to validate your EKS resilience plan.

Costs and lifecycle management

With AWS EKS, you pay for the managed control plane and the worker nodes you run. The control plane cost is relatively constant, while you control costs on worker nodes through instance types, bidding strategies (for spot instances where appropriate), and auto-scaling configurations. Monitoring usage and rightsizing resources can significantly reduce expenses. If workloads are intermittent, Fargate can be a cost-effective option for running pods without dedicated instances, though it may come with different pricing characteristics than managed node groups.

Clean up and next steps

When you finish a test or a demo, remember to clean up resources to avoid continuing charges. Delete the deployed Kubernetes objects, scale down and terminate worker nodes, and finally delete the EKS cluster with:

eksctl delete cluster --name my-eks-cluster --region us-west-2

As you continue exploring AWS EKS, experiment with more advanced patterns: multi-cluster deployments, service mesh (such as Istio or AWS App Mesh), secure ingress, and blue/green deployments. Each enhancement reinforces the real-world readiness of your Kubernetes workloads on AWS EKS.

Conclusion

AWS EKS provides a robust, scalable path to running Kubernetes in the cloud with the convenience of a managed control plane. By starting with a simple cluster, deploying a quick sample app, and progressively adding security, observability, and AWS-native integrations, you can build a production-ready workflow that aligns with Google SEO-friendly, user-focused documentation standards. Whether you are migrating from self-managed Kubernetes or building a new application from scratch, AWS EKS helps you modernize deployment pipelines while staying aligned with best practices in reliability, security, and efficiency.