EKS Cost optimization is important because when you run a Kubernetes cluster in the cloud, it involves many parts, and each part can add up in cost. If you’re not careful, you might pay more than necessary for unused capacity, inefficient scaling, or underutilized resources.
In this article, you’ll find what Amazon EKS is, understanding the EKS pricing and what are the best practices for EKS cost optimization. So, let's dig in!
What is Amazon EKS?
Amazon Elastic Kubernetes Service (EKS) is a managed service that makes it easier to run Kubernetes on AWS. With EKS, you don’t have to worry about installing or managing the Kubernetes control plane; AWS handles that for you while you focus on running your containerized applications.
Understanding EKS Pricing
Understanding the EKS pricing is important to control the costs. Let’s understand:
1. EKS Control Plane Costs
The EKS control plane is the heart of your cluster. AWS manages the control plane for you, and you pay a fixed fee for this service. This fee covers core functions such as API operations and cluster management. With a managed control plane, you get a reliable, fully maintained service, but you also pay a premium for that convenience. On the other hand, self-managed control planes can be more flexible in cost, but they require more hands-on work to set up, manage, and secure.
2. Worker Node Costs
You run your applications on Worker nodes, and you have two main options: EC2 instances and Fargate.
EC2 Instances: When you use EC2, you control the instance types, sizes, and purchase options. This flexibility lets you choose options like on-demand, reserved, or spot instances. Spot instances can save you money, but they might be interrupted. Reserved instances and Savings Plans offer discounts when you commit to steady use over time.
Fargate: Fargate is a serverless compute option that charges per pod based on resource usage. This removes the need to manage EC2 instances, but it can be more expensive for steady, predictable workloads. Fargate is great for unpredictable loads or when you want to simplify operations.Behind the scenes each Fargate pod runs in its own isolated virtual machine, enhancing security.
3. Storage and Network Costs
EKS uses various storage options and network resources, and each has its own cost:
Persistent Storage Costs:
EBS: Most of the Kubernetes clusters use EBS volumes for block storage. It is reliable but costs can add up if volumes are over-provisioned.
EFS: EFS is a good option for shared file storage that scales automatically, though it may be pricier than EBS.
FSx: If you need high-performance or Windows-based file storage, FSx is available, with different pricing.
Network Traffic Costs:
Intra-zone vs. Inter-zone Traffic: The thing you should know is that data transferred within the same Availability Zone is generally cheaper than traffic crossing zones. So plan your network accordingly and keeping traffic local can help reduce these charges.
4. Additional Costs
There are other expenses you should keep in mind, like:
Load Balancers: When you use load balancers to distribute traffic, they come with their own charges. The cost depends on the number of load balancers and the amount of data they handle.
Logging and Monitoring: The tools like CloudWatch collect logs and metrics from your cluster. While these tools are great for managing your environment, they can also add to your costs if not configured carefully.
Best Practices for EKS Cost Optimization
Here are some of the best practices that you can follow:
1. Choosing the Right Compute Option
2. Rightsizing Worker Nodes and Clusters
3. Efficient Pod Scheduling
4. Optimizing Storage Costs
5. Reducing Network Costs
6. Cost-Effective Monitoring and Governance Strategy
7. FinOps and Cost Visibility in EKS
Now, let’s discuss one by one these best practices in detail:
1. Choosing the Right Compute Option
a. On-Demand vs. Spot Instances
EKS clusters run on compute resources, either EC2 instances or Fargate. On-demand instances give you full flexibility with less management overhead, but they come at a higher cost. Spot instances, on the other hand, are available at a lower price since they use spare capacity. However, they can be interrupted with little notice, so they’re best used for stateless or fault-tolerant workloads. For many users, mixing both on-demand and spot helps maintain a balance between cost savings and reliability.
Beyond the basic choice, effective spot instance strategies can help you further enhance the cost optimization. You should design your workloads to be resilient by implementing checkpointing or maintaining a backup pool of on-demand instances. In this way, your applications can gracefully handle interruptions without disruption and quickly shift to an on-demand backup. And you can also use AWS’s capacity-optimized allocation strategy that allows EKS clusters to automatically select spot instance pools with the highest available capacity, helping in reducing the risk of interruption while still taking full advantage of the lower pricing. This approach means that you’re not only saving on costs but also achieving a higher level of operational stability when using spot instances.
b. Savings Plans and Reserved Instances
When your workloads are predictable, Savings Plans and Reserved Instances offer deep discounts compared to on-demand pricing. Savings Plans commit you to a consistent amount of usage over a period (usually one to three years), while Reserved Instances work similarly but are tied to a specific instance type. These options can reduce your compute costs if your usage is steady and predictable.
c. Fargate vs. EC2 Cost
Fargate provides a serverless compute model where you pay per pod, removing the overhead of managing EC2 instances. This is good for variable workloads or when you want to avoid infrastructure management. However, if your workload is steady or you have predictable, high utilization, EC2 instances might be more cost-effective. The choice largely depends on the workload’s nature, the management overhead you’re willing to accept, and your ability to optimize instance utilization.
2. Rightsizing Worker Nodes and Clusters
a. Optimal Instance Types for Different Workloads
Choosing the right instance type is important. For CPU-intensive workloads, you might choose compute-optimized instances, whereas for memory-intensive applications, you should choose memory-optimized types. It is really important to understand your workload’s performance characteristics to ensure that you don’t over-provision (which wastes money) or under-provision (which causes performance). Making these decisions is highly complex because there are so many instance types to choose from. PerfectScale node recommendations make this easy.
b. Horizontal vs. Vertical Scaling Considerations
Horizontal scaling means adding more pods, hence more nodes. It can improve resilience and allow for workload distribution. Vertical scaling using larger instances, might be easy to manage but can be less flexible and might not use resources as efficiently. A combination of both approaches is best: horizontal scaling for handling bursty traffic and vertical scaling to meet consistent demand.
>> Take a look at Horizontal vs. Vertical Autoscaling
c. Cluster Autoscaler vs. Karpenter for Autoscaling
Karpenter is a next-generation autoscaling tool that rethinks how EKS clusters manage their node capacity. Unlike the Kubernetes Cluster Autoscaler which depends upon pre-set thresholds and defined nodegroups, Karpenter continuously monitors your cluster in real time and responds immediately to changes in workload. By dynamically launching or terminating nodes as needed, it ensures that you’re always running the optimal number of instances.
A key advantage of Karpenter is its ability to select the most appropriate instance types based on your specific application requirements. This means that instead of over-provisioning with one-size-fits-all nodes, Karpenter can provision smaller, cost-effective nodes during peak demand and quickly shut them down when they’re no longer needed. For example, in scenarios where your workload spikes during business hours and drops off at night, Karpenter’s fine-grained scaling ensures you only pay for the compute power you actually use resulting in cost savings and improved resource utilization.
d. EKS Auto Mode
EKS Auto Mode is designed to simplify cluster management by automatically adjusting resources based on your workload demands. This mode not only reduces the manual effort required to manage scaling but also helps prevent over-provisioning making sure you only pay for what you use. The operational benefits provide a more responsive infrastructure that adapts to traffic spikes and lulls(when there’s less demand). Although there might be a slightly higher cost associated with automation but the gains in efficiency and reliability outweigh this expense, making it a smart choice for dynamic environments.
>> Take a look at EKS Auto Mode in Real Life
Further, PerfectScale enhances Kubernetes autoscaling and cost management by integrating with tools like Karpenter, KEDA, and the core Kubernetes autoscaling mechanisms (HPA and Cluster Autoscaler). PerfectScale provides data-driven insights by analyzing historical usage patterns and current resource utilization, offering actionable recommendations to ensure that autoscaling settings are optimized for cost efficiency.
3. Efficient Pod Scheduling
a. Bin-Packing Strategies
The efficient pod scheduling is important to maximizing the utilization of your nodes. Bin-packing involves organizing pods on nodes in such a way that you maximize resource usage without exceeding capacity. By carefully planning how pods are distributed, you can reduce wasted CPU and memory which results in lowering costs.
b. Node Affinity and Taints/Tolerations for Optimal Resource Allocation
Kubernetes provides mechanisms like node affinity and taints/tolerations to control pod placement. Node affinity allows you to specify which pods should run on which nodes based on labels, and Taints and tolerations let you repel certain pods from nodes unless they explicitly tolerate the taint. Together, these strategies help ensure that workloads are placed on the most appropriate and cost-effective nodes.
>> Learn in detail about Taints and Tolerations in Kubernetes
c. Scheduling Batch Workloads Efficiently
You know that not all workloads need to run 24/7. For example, Batch jobs can be scheduled during off-peak hours when compute costs might be lower. By intelligently scheduling these tasks, you can reduce the number of resources required during high-cost periods and optimize your overall spend.
4. Optimizing Storage Costs
a. Right-Sizing EBS Volumes
The storage can represent a significant cost in your EKS environment. It’s important to right-size your EBS volumes to match your actual needs rather than over-allocating. You should monitor the usage and adjust volume sizes accordingly. You should avoid keeping large, underutilized volumes that you’re paying for unnecessarily.
b. EFS vs. FSx vs. S3 Considerations
The different storage solutions come with varying cost profiles and performance characteristics. Let’s discuss:
EFS (Elastic File System): It is ideal for workloads that need a shared file system with the ability to scale automatically. It is more expensive but provides high availability and durability.
FSx: This offers high-performance file storage used for Windows-based applications or high-throughput workloads.
S3: Although it is not a direct replacement for file systems in a cluster, S3 is highly cost-effective for storing large amounts of data that don’t require the same performance as block storage.
You should choose between these based on your application’s performance needs, high availability, and your budget constraints.
5. Reducing Network Costs
a. Cross-AZ Traffic Minimization
When your EKS clusters span multiple Availability Zones (AZs), inter-AZ data transfer costs can add up quickly. To keep these costs under control, you should try to design your applications so that most traffic stays within a single AZ. This involves deploying certain workloads in the same AZ or configuring your networking to reduce cross-AZ communication.
b. Using VPC Endpoints
VPC endpoints allow you to privately connect your VPC to supported AWS services without using an Internet gateway or NAT device. This not only increases security but can also reduce data transfer costs by keeping traffic within the AWS network. You should implement VPC endpoints for services like S3 and DynamoDB, it can help streamline network traffic and lower costs.
c. Ingress and ALB Controller
You should also consider how you route incoming traffic. Instead of creating a separate LoadBalancer service for each application, using an ingress controller with the AWS Application Load Balancer (ALB) can be a better option. This approach centralizes traffic management, reduces the number of public endpoints, and simplifies routing rules. In turn, it helps lower network costs and makes your infrastructure easier to manage overall.
6. Cost-Effective Monitoring and Governance Strategy
a. Using AWS Cost and Usage Reports (CUR)
AWS Cost and Usage Reports (CUR) provide a comprehensive view of your AWS spending that includes a detailed breakdown of costs for services and resources important to your EKS environment. To set up CUR for EKS, start in the AWS billing console by creating a new report, and configure it to include resource-level details that cover control plane operations, worker nodes, storage, and data transfer. You can save this report to an S3 bucket for further analysis. It is best practice to schedule CUR generation regularly to catch emerging cost trends early. Also, you should ensure that the S3 bucket is secured with appropriate permissions and lifecycle policies to manage storage costs effectively. Once CUR is set up, you can find insights such as the breakdown of expenses by specific EKS components, identify usage trends over time, and utilize cost allocation tags to attribute expenses to individual teams or projects, aiding in effective chargeback and budget adherence.
To further streamline cost management, PerfectScale's AWS CUR integration enables you to retrieve precise Kubernetes cost data, incorporating Reserved Instances, Savings Plans, and Discounts. By providing real-time cost updates and accurate chargeback reporting, it delivers deeper insights into your K8s spending, allowing you to optimize costs effectively.
b. CloudWatch and Prometheus for Cost Metrics
Amazon CloudWatch is a service that monitors and manages applications and resources for AWS. With the help of this, you can configure custom dashboards and track different metrics such as control plane operations, EC2 instance utilization, storage consumption, and network data transfers. This visual representation of your EKS resource usage helps you quickly identify trends, detect cost anomalies, and pinpoint areas where resources might be under- or over-utilized. You can set automated alarms in CloudWatch to notify you when spending exceeds predefined thresholds.
You can also integrate Prometheus with CloudWatch to collect real-time metrics from your Kubernetes pods. Then, you can connect Prometheus with Grafana to visualize these metrics in detail. This setup lets you see which pods or services are costing the most and helps you adjust resource use and scaling strategies.
c. AWS Cost Anomaly Detection
AWS Cost Anomaly Detection is important for cost monitoring in resource-intensive workloads like EKS. It uses machine learning to continuously compare your spending against historical trends and preset baselines, automatically alerting you to unexpected spikes such as in control plane costs, worker node usage, or data transfer, so issues can be addressed before they escalate.
To set it up, first ensure you have detailed cost data from AWS Cost and Usage Reports (CUR) configured at the resource level. Then, enable Cost Anomaly Detection via the AWS Cost Management dashboard, where you define thresholds and customize alert sensitivity. If your costs exceed these limits, notifications are sent via email, Amazon SNS, or other alerting mechanisms.
7. FinOps and Cost Visibility in EKS
a. Monitoring Cost Breakdowns
You should understand exactly where your money is spending. You should utilize tools like AWS Cost Explorer and CloudWatch to gain a granular view of your spending.
b. Cost Allocation Tags and Chargeback Models
You should assign cost allocation tags to your resources that allow you to attribute costs to specific teams, projects, or business units. With detailed tagging, you can implement chargeback or showback models, making each team accountable for its resource usage. This not only improves transparency but also motivates teams to optimize their own workloads and avoid unnecessary expenses.
Leverage PerfectScale by DoiT
You should integrate PerfectScale into your EKS management strategy, which empowers you to optimize both performance and cost across your Kubernetes environment. With PerfectScale, your workloads are continuously analyzed to detect underutilized resources and performance risks, enabling automatic right-sizing that aligns resource allocation with actual usage. This means that your clusters are always tuned to run efficiently, reducing waste and ensuring that you're only paying for the capacity you truly need. PerfectScale also provides detailed, actionable insights into node-level performance, helping you identify the best configurations for your specific applications. Overall, by adopting PerfectScale, you simplify the complexities of Kubernetes management and create a unified, cost-effective solution that enhances both operational performance and budget control in your EKS environment.
Final Thoughts
In conclusion, managing costs in your EKS environment is all about understanding each part of your setup and making smart choices. You’ve seen everything add costs, from control plane to storage, and additional services. By choosing the right compute options, right-sizing resources, and using tools for real-time monitoring and cost governance, you can save money and keep your system running smoothly. Whether it’s mixing on-demand and spot instances, fine-tuning autoscaling with Karpenter, or using PerfectScale by DoiT for ongoing optimization, every step helps you pay only for what you truly need. We hope this guide gives you clear control of your EKS costs and helps you build a reliable and cost-effective Kubernetes environment.
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