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Enterprises waste up to 35% of their entire cloud budget, and bloated, oversized containers are one of the biggest reasons why. If you’re running Amazon EKS, you’re operating in one of the richest environments for unnecessary spend: idle nodes, over-provisioned instances, and clusters quietly billing you around the clock.
The fix isn’t complicated, but it does require knowing what you’re actually paying for. Here’s the complete breakdown of Amazon EKS pricing, and how to make sure every dollar you spend is earning its place.
Amazon Elastic Kubernetes Service (EKS) is a managed service that makes it easier to run Kubernetes on AWS and on-premises. Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications. Amazon EKS automatically manages the Kubernetes control plane for you, which includes the API servers and the etcd database where cluster data is stored.
Running Kubernetes as a managed service reduces the complexity of the Kubernetes environment, automating cluster setup, administrative tasks, and ensuring the underlying infrastructure is always up to date. EKS provides three options for provisioning Kubernetes cluster nodes—Elastic Compute Cloud (EC2) instances, Fargate (Amazon’s serverless compute service), and Outposts (specialized hardware that runs AWS resources on-premises).
In AWS EKS, you pay for AWS resources, such as EC2 instances or EBS volumes, which you provision to run your Kubernetes nodes. You are charged for each hour or partial hour you run each Amazon EKS cluster. Below we break down EKS pricing components, including the control plane fee (standard vs. extended support), optional control plane and add-on charges, and node/runtime models like EC2, Fargate, Outposts, Auto Mode, and Hybrid Nodes.
A practical estimate looks like:
Monthly EKS cost ≈ (Cluster hours × control plane fee)
AWS notes you pay for the EKS cluster fee plus the other AWS services you use (for example EC2, EBS, public IPv4).
Before you estimate node costs, it helps to separate what AWS charges for the EKS control plane from optional EKS add-ons/features, and then from the compute model you run your workloads on.
If you opt into Provisioned Control Plane, AWS charges an additional hourly rate on top of the standard/extended support cluster fee:
With EKS Auto Mode, AWS launches and manages EC2 instances for you and charges an additional Auto Mode management fee:
If you enable EKS Capabilities, AWS bills two hourly components:1) A base hourly rate for each enabled capability2) Hourly usage charges based on what’s managed:
With EKS Hybrid Nodes, AWS charges by vCPU-hour (tiered by total monthly usage in a region/account):
EC2, or Elastic Compute Cloud, is one of the most popular services provided by AWS. It offers secure, resizable compute capacity in the cloud. EKS lets you run Kubernetes nodes on Amazon EC2 instances.
When it comes to Amazon EKS pricing with Amazon EC2, you pay $0.10 per hour for each Amazon EKS cluster that you create. You can use a single Amazon EKS cluster to run multiple applications by taking advantage of Kubernetes namespaces and IAM security policies. In addition to the cluster management fee, you will also pay for the EC2 instances and other resources, such as EBS volumes, used by your applications.
Example estimate (plug in today’s instance price for your region):
Monthly cost ≈ (730 × EKS control plane fee)
For a 730-hour month, the control plane portion alone is:
Fargate is a serverless compute engine for containers that works with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). AWS Fargate removes the need to provision and manage servers, lets you specify and pay for resources per application, and improves security through application isolation by design.
With Amazon EKS on AWS Fargate, you pay the $0.10 per hour cluster management fee, and in addition pay only for the vCPU and memory resources that your pod needs to run. This allows you to precisely measure and manage your costs. Fargate resources are billed per second and have a 1-minute minimum.
Example estimate (Fargate rates vary by region):
Monthly cost ≈ (cluster_hours × EKS control plane fee)
Fargate is billed per second with a 1-minute minimum (based on the time from image pull start until the pod terminates).
AWS Outposts is a fully managed service that extends AWS infrastructure, AWS services, APIs, and tools to virtually any data center, co-location space, or on-premises facility. It allows you to run AWS services, such as EKS an EC2, within your on-premises data center.
The pricing for running Amazon EKS on AWS Outposts varies depending on the Outpost configuration you have. You pay for the Outpost capacity that you have ordered irrespective of how you utilize it. In addition to the Outpost capacity costs, there’s a separate charge for EKS, which is $0.10 per hour per EKS cluster, similar to running EKS in the cloud.
Example estimate (Outposts):
Monthly cost ≈ (cluster_hours × EKS cluster fee for your Outposts deployment type)
Note: EKS local clusters on AWS Outposts use the standard EKS cluster fee and do not have extended Kubernetes version support.
Itiel Shwartz
Co-Founder & CTO
In my experience, here are tips that can help you better manage and optimize costs when using Amazon EKS:
Regularly review and adjust the size of your EC2 instances to match your workload requirements.
Use Spot Instances for non-critical and fault-tolerant workloads to save up to 90% on compute costs.
Commit to a consistent amount of usage with AWS Savings Plans to reduce costs across EC2, Fargate, and Lambda.
Configure Cluster Autoscaler to dynamically adjust the number of nodes based on demand, avoiding over-provisioning.
Utilize tools like AWS Cost Explorer and third-party solutions to gain visibility into your Kubernetes spending and optimize resource usage.
Optimizing your AWS EKS pricing starts with evaluating the size and type of instances you need based on your applications’ requirements. Choosing the right instance types and sizes for your worker nodes is crucial. You should assess your workloads to determine the compute, memory, and storage needs and select the instance types that best match these requirements.
Avoid over-provisioning resources to prevent unnecessary costs. AWS offers a variety of EC2 instance types that are optimized for different workloads, such as compute-optimized, memory-optimized, and storage-optimized instances. As an alternative, use Amazon Fargate, which bills according to actual resources used by your pods.
Amazon EKS Managed Node Groups simplify the process of managing worker nodes. These groups automatically adjust the number of nodes in your cluster to meet your application’s needs, ensuring that you have the right amount of resources to handle your workload without over-provisioning.
This feature helps optimize costs by scaling down resources during low-traffic periods and scaling up during peak times. Managed Node Groups also handle updates and patches for your nodes, ensuring your environment is secure and efficient.
For workloads with predictable usage patterns, purchasing Reserved Instances or Savings Plans can offer significant cost savings over on-demand pricing. Reserved Instances allow you to commit to a specific instance type and size for a 1-year or 3-year term, offering a lower hourly rate compared to on-demand instances.
Similarly, AWS Savings Plans provide a flexible way to save on compute usage across EC2, Fargate, and Lambda, in exchange for a commitment to a consistent amount of usage (measured in $/hour) for a 1-year or 3-year term. Both options can lead to cost reductions of up to 72% compared to on-demand rates.
Learn more in our detailed guide to Kubernetes cost reduction.
AWS Spot Instances let you take advantage of unused EC2 capacity at a significant discount compared to on-demand prices. Spot instances are primarily suited for stateless and fault-tolerant workloads, because they can be interrupted by AWS with only two minutes’ notice.
By integrating Spot Instances into your EKS clusters, you can reduce compute costs for suitable workloads by up to 90%. It’s important to implement strategies to manage interruptions and maintain your application’s availability and performance, an area where AI SRE agents are increasingly being used to detect and respond to node disruptions automatically.
AWS Budgets allows you to set custom budget thresholds and receive alerts when your costs or usage exceed these thresholds. This tool is essential for managing your AWS spending effectively.
By setting up budgets for your EKS clusters, you can monitor your expenses in real time and adjust your resources accordingly to avoid unexpected charges. Alerts can be configured to notify teams via email or SMS, enabling proactive Kubernetes cost management, though teams dealing with high alert volumes are increasingly looking at how AI SRE tooling can reduce operational toil and cut response times at scale.
Several Kubernetes cost management tools are available to help you understand and optimize your cluster costs. These tools provide visibility into your Kubernetes spending, breaking down costs by namespace, service, and label.
By identifying high-cost resources and potential inefficiencies, you can make informed decisions to optimize your cluster configuration and reduce expenses. Tools such as AWS CloudWatch Container Insights for Kubernetes offer detailed insights and recommendations for cost optimization within your EKS environment.
Komodor’s cost optimization suite ensures visibility, optimization and responsible Kubernetes growth without compromising on performance, all from the same Kubernetes platform you know and love.
Learn more about Komodor’s Kubernetes cost optimization capabilities or get started now!
Amazon EKS (Elastic Kubernetes Service) is a managed AWS service that automates the deployment, scaling, and management of containerized applications using Kubernetes. It handles the Kubernetes control plane, including API servers and the etcd database, so you don’t have to, and supports node deployment via EC2, Fargate, or Outposts.
Amazon EKS charges $0.10 per cluster per hour, plus the cost of underlying resources like EC2 instances or EBS volumes. On Fargate, you also pay per vCPU and memory used. Clusters running on unsupported Kubernetes versions under extended support are charged $0.60 per cluster per hour.
The cheapest option is AWS Spot Instances, which offer up to 90% savings over on-demand pricing. They’re best for stateless or fault-tolerant workloads. For predictable workloads, Reserved Instances or Savings Plans can cut costs by up to 72%. Using Fargate eliminates idle resource costs by billing only for actual pod usage.
With EC2, you manage and pay for the virtual machines running your Kubernetes nodes. With Fargate, AWS handles the infrastructure entirely, and you only pay for the vCPU and memory your pods actually consume, billed per second with a one-minute minimum, making it ideal for variable or unpredictable workloads.
Key strategies include: right-sizing EC2 instances, using Managed Node Groups for auto-scaling, purchasing Reserved Instances or Savings Plans for predictable workloads, leveraging Spot Instances for fault-tolerant tasks, setting AWS Budget alerts, and using Kubernetes cost management tools like CloudWatch Container Insights to identify and eliminate waste.
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