What is Amazon EKS?

Amazon Elastic Kubernetes Service (EKS) is AWS's managed Kubernetes offering that handles the complex work of running container orchestration infrastructure, freeing teams to focus on building applications rather than maintaining clusters. It's become the go-to choice for organizations running containerized workloads on AWS, from startups deploying their first microservices to enterprises managing thousands of containers.

This guide covers how EKS works, the benefits it offers over self-managed Kubernetes, common use cases, and how to get started with your first cluster.

What is Amazon EKS

Amazon Elastic Kubernetes Service (EKS) is a managed service from AWS that makes it easier to run Kubernetes on cloud infrastructure without installing or operating your own Kubernetes control plane. The control plane is essentially the brain of a Kubernetes cluster—it decides where applications run, monitors their health, and responds when things go wrong. AWS handles all of that complexity, so developers can focus on building and deploying applications.

If you're new to containers, think of them as lightweight packages that bundle an application with everything it requires to run. Kubernetes is the open-source system that orchestrates those containers, deciding which servers run which applications and scaling them up or down based on demand.

• Amazon EKS: A managed Kubernetes service running on AWS infrastructure
• Kubernetes: An open-source platform for automating container deployment and scaling
• Control plane: The management layer that AWS operates on your behalf
• EKS Auto Mode: A feature that creates production-ready clusters with one click

EKS also offers Auto Mode, which simplifies cluster creation even further. Rather than configuring networking, compute, and storage separately, Auto Mode handles all of it automatically, including ongoing patching and scaling.

How Amazon EKS works with Kubernetes

EKS is AWS's implementation of Kubernetes, and the relationship between them is straightforward. AWS manages the control plane, which includes the master nodes responsible for scheduling workloads and tracking cluster state. You manage the worker nodes where your applications actually run, though even worker node management can be automated using AWS Fargate.

A few concepts are helpful here. A cluster is your complete Kubernetes environment, combining the control plane with worker nodes. Pods are the smallest units you deploy—each pod contains one or more containers that share resources. Nodes are the machines, either virtual or physical, that run your pods.

You interact with EKS using kubectl, the standard Kubernetes command-line tool. Because EKS runs standard Kubernetes, the skills you develop transfer directly to any other Kubernetes environment, whether on another cloud provider or in your own data center.

Key benefits of Amazon EKS

Organizations adopt EKS for practical reasons tied to operational efficiency and application reliability.

Simplified Kubernetes cluster management

AWS takes care of the operational work that typically comes with running Kubernetes. Upgrades, security patches, and high availability across multiple data centers all happen automatically. Your team can skip the complexity of maintaining Kubernetes infrastructure and spend that time on application development instead.

Enhanced security and compliance

EKS integrates directly with AWS Identity and Access Management (IAM), which allows fine-grained control over who can access what. Clusters run inside your Virtual Private Cloud (VPC), providing network isolation from other AWS customers. Encryption protects data both at rest and in transit, and EKS maintains compliance certifications including SOC, PCI, and HIPAA.

High availability and automatic scaling

The EKS control plane runs across multiple availability zones by default, so a failure in one zone doesn't bring down your cluster. Worker nodes can scale up during traffic spikes and scale back down when demand drops. This architecture keeps applications available even when individual components fail.

Seamless integration with AWS services

EKS connects naturally with other AWS services. Amazon CloudWatch handles monitoring, AWS Load Balancers distribute traffic, and Amazon ECR stores container images. These native integrations reduce the custom configuration work that would otherwise be required.

Cost-effective container orchestration

You pay for the compute resources your applications consume, with no upfront commitments required. Spot instances can reduce costs significantly for workloads that tolerate interruption. EKS Auto Mode simplifies pricing by bundling control plane and compute costs together.

Common use cases for Amazon EKS

EKS serves a variety of workload types, each benefiting from container orchestration in different ways.

Microservices architecture

Breaking large applications into smaller, independent services is where Kubernetes excels. Each microservice can scale on its own, deploy on its own schedule, and fail without affecting the rest of the application. EKS provides the orchestration that makes managing dozens or hundreds of services practical.

Machine learning and AI workloads

Data science teams use EKS to deploy machine learning models and run training pipelines. Containers ensure that code behaves the same way in development as it does in production. GPU-enabled nodes support compute-intensive training, while inference workloads scale based on incoming requests.

Batch processing and big data

Jobs that process large datasets benefit from EKS's ability to provision compute resources on demand. Once processing finishes, those resources scale back down. This elastic approach proves more economical than maintaining servers that sit idle between jobs.

Hybrid cloud deployments

Organizations with on-premises requirements can extend Kubernetes workloads across environments. EKS Anywhere, covered later in this article, enables consistent management whether workloads run in AWS, a private data center, or at edge locations.

Web application hosting

Modern web applications with unpredictable traffic patterns fit naturally on EKS. The platform handles sudden traffic increases through automatic scaling while keeping costs reasonable during quieter periods.

Amazon EKS vs Amazon ECS

AWS offers two primary container orchestration services. The choice between them often depends on your team's existing experience and future plans.

Feature	Amazon EKS	Amazon ECS
Orchestration engine	Kubernetes (open-source)	AWS-native
Multi-cloud portability	High—Kubernetes runs anywhere	Limited to AWS
Learning curve	Steeper for Kubernetes newcomers	Gentler for AWS-native teams
Community and ecosystem	Extensive Kubernetes ecosystem	AWS-specific tooling
Best fit	Teams with Kubernetes experience or multi-cloud plans	Teams focused exclusively on AWS

ECS offers a simpler path for teams already comfortable with AWS services who don't anticipate running workloads on other cloud providers. EKS makes more sense when portability matters or when you want access to the broader Kubernetes ecosystem of tools and extensions.

Amazon EKS vs self-managed Kubernetes

Running your own Kubernetes clusters provides maximum control, though that control comes with significant operational responsibility.

Aspect	Amazon EKS	Self-Managed Kubernetes
Control plane management	AWS handles it	Your responsibility
Patching and upgrades	Automated	Manual process
Initial setup	Streamlined	Requires deep expertise
Customization	Some constraints	Complete flexibility
Operational overhead	Reduced	Substantial

Self-managed Kubernetes might appeal to organizations with very specific customization requirements and dedicated platform engineering teams. For most organizations, however, the operational burden of managing Kubernetes infrastructure outweighs the benefits of complete control.

What is AWS EKS Anywhere

EKS Anywhere extends the EKS experience to your own data centers and edge locations. You get the same Kubernetes distribution, APIs, and tooling that run in AWS, but on infrastructure you own and operate.

This matters for organizations with data residency requirements, latency-sensitive applications, or significant existing data center investments. Both cloud and on-premises clusters can be managed through consistent workflows, which reduces complexity for platform teams supporting multiple environments.

• On-premises deployment: Run EKS in your own data centers using the same tools as cloud EKS
• Edge computing: Deploy clusters closer to end users for lower latency
• Consistent experience: The same APIs and management approach work across all environments

How to get started with Amazon EKS

Getting your first cluster running involves a series of straightforward steps.

1. Create your AWS account and IAM roles

You'll start with an AWS account and appropriate IAM roles that allow EKS to manage resources on your behalf. AWS provides service-linked roles that simplify this initial setup.

2. Set up your EKS cluster

The AWS Console offers a guided experience for cluster creation. Alternatively, eksctl is a command-line tool built specifically for EKS that can create a cluster with a single command. EKS Auto Mode reduces the process even further, handling compute, networking, and storage configuration automatically.

3. Configure kubectl for cluster access

After creating your cluster, you'll update your local kubectl configuration to connect to it. The AWS CLI can generate this configuration automatically, so you don't have to write it by hand.

4. Deploy your first containerized application

With kubectl configured, you can deploy applications using standard Kubernetes manifests. Starting with something simple, like a basic web server, helps verify that everything works correctly before moving to more complex deployments.

5. Monitor performance and scale resources

Amazon CloudWatch collects metrics from your cluster automatically. Kubernetes-native tools like the metrics server enable autoscaling based on CPU usage, memory consumption, or custom metrics you define.

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FAQs about Amazon EKS

What does EKS stand for?

EKS stands for Elastic Kubernetes Service. The term "elastic" refers to the ability to scale resources up and down based on demand, which is a core characteristic of cloud computing services.

Why use Amazon EKS instead of EC2 for containerized applications?

EC2 provides virtual machines, but running containers on EC2 means installing and managing Kubernetes yourself. EKS provides the orchestration layer that handles scheduling, scaling, and self-healing for containerized workloads. Building those capabilities on raw EC2 instances would require significant engineering effort.

How does Amazon EKS pricing work?

You pay $0.10 per hour for each EKS cluster control plane, plus the cost of compute resources for your worker nodes. EKS Auto Mode bundles these costs differently, charging based on the compute resources you actually consume rather than separating control plane and worker node costs.

Is Amazon EKS included in the AWS free tier?

The EKS control plane is not part of the AWS free tier. However, you can use free tier eligible EC2 instances for worker nodes, which helps reduce costs while learning the platform.

What is the difference between Amazon EKS and Azure AKS?

Both are managed Kubernetes services from major cloud providers. EKS runs on AWS and integrates with AWS services, while Azure Kubernetes Service (AKS) runs on Microsoft Azure with Azure-native integrations. The core Kubernetes experience is similar across both platforms, though each has unique features and pricing structures.