Last week, in the first part of our two-part blog, we looked at the different components that contribute to your Amazon Elastic Kubernetes Service (EKS) costs.

In this part of our guide, we explore various cost optimization strategies that can help you maximize the efficiency of your Amazon EKS deployment. From rightsizing your EKS cluster and leveraging hardware choices like AWS Graviton processors to making informed purchase decisions and utilizing auto-scaling, these strategies empower you to strike the perfect balance between cost-effectiveness and high performance.

Cost optimization strategies

1. Rightsizing Your EKS Cluster: 

Container Resource Requests and Limits: Defining resource requests and limits for containers ensures efficient allocation of CPU and memory. Accurate specifications prevent underutilization or overcommitment, both of which can lead to increased costs.- Waste Reduction: Careful configuration and management of container resources minimize waste. Unused or underused resources translate into extra expenses.- Serverless Container Management with AWS Fargate: AWS Fargate allows you to run containers without managing the underlying infrastructure. This can help save costs by precisely matching resources to your workload requirements.– EBS Volume Management: Effective management of Elastic Block Store (EBS) volumes involves selecting the right type and size for your storage needs, and deleting unneeded volumes to avoid incurring unnecessary costs.

2. Hardware: AWS Graviton Processor:

Custom-Built by AWS: AWS Graviton processors are custom-built with 64-bit Arm cores for optimized performance.– Graviton3 Performance: Graviton3 offers up to 25% higher compute performance than Graviton2, using up to 60% less energy. It also features DDR5 memory, delivering 50% more memory bandwidth.– Graviton2 Cost-Performance: Graviton2 provides up to 40% better price performance compared to x86_64 processors, powering various Amazon EC2 instance families.– Amazon EKS Support: Amazon EKS supports Graviton processors, offering ARM64-optimized AMIs with the same release cadence as x86_64. It also allows for multi-architecture image building.

3. Purchase Options:

Understanding AWS purchase options and leveraging them strategically is a key aspect of EKS cost optimization.– On-Demand Instances: Pay for compute capacity by the second without long-term commitments, ideal for spiky workloads, to define needs for stateful workload, offering reliability without long-term commitments.– Savings Plans: Make a 1- or 3-year commitment and receive a significant discount off On-Demand prices, suited for predictable workloads, ensuring cost predictability.– EC2 Spot Instances: Up to 90% cost savings, suitable for fault-tolerant, stateless workloads with intermittent usage.- EC2 Spot Instance Price and Capacity Optimized with Karpenter a. New Strategy for Spot Instance Allocation: Karpenter v0.19.0+ introduces an advanced EC2 Spot Instance allocation strategy by default. b. Ideal for Diverse Workloads: This strategy is a versatile choice, suitable for various Spot Instance use cases, especially Kubernetes workloads. c. Balanced Selection: It selects Spot Instances based on both available spare capacity and price, striking a balance between resource availability and cost savings. d. Low Interruption Rate, Lower Total Cost: The strategy maintains a low interruption rate similar to capacity-optimized instances while significantly reducing your total EC2 expenses.

4. Auto Scaling: Leveraging Third-Party Tools:

In addition to AWS native auto-scaling capabilities, consider third-party tools like Karpenter for fine-tuned control over your Amazon EKS auto-scaling strategies. Karpenter offers the following advantages:– Open Source and Flexible: Karpenter is an open-source tool that provides flexibility in scaling your EKS clusters. It allows you to tailor your scaling policies to match your specific workload requirements.– AWS Support: Karpenter is fully supported by AWS in Amazon EKS clusters, ensuring compatibility and a reliable experience in your EKS environment.– Integration with Kubernetes Scheduler and EC2: Karpenter seamlessly integrates with the Kubernetes scheduler and EC2 instances, enabling dynamic scaling based on real-time resource demands.– Rightsized Node Launch: It excels in launching right-sized nodes in response to unscheduled pods, allowing you to match your node resources precisely with your application requirements.– Native Kubernetes Scheduling Constraints: Karpenter natively works with Kubernetes scheduling constraints, including node label selectors, pod affinity, and topology spread constraints, ensuring your pods are placed optimally.– Efficient Node Termination: Karpenter actively manages your cluster by terminating unused nodes and consolidating pods, leading to reduced costs and efficient resource utilization.Karpenter simplifies incorporating AWS Graviton and EC2 Spot Instances to improve cluster utilization and lower costs.By incorporating Karpenter into your EKS environment, you gain an additional layer of control and precision in your auto-scaling efforts, enabling a more cost-effective and optimized cluster.

Remember that optimizing EKS costs is an ongoing journey. Regularly review and fine-tune your strategies to adapt to changing workloads and technology advancements. Keep an eye on AWS innovations and emerging best practices to stay ahead in the world of cost-efficient container orchestration.

With these principles at your disposal, you are well-equipped to navigate the complexities of EKS and drive your organization’s success in the cloud-native era.

To know more about how CloudifyOps, an AWS Advanced Consulting Partner, can help you optimize your cloud costs, write to us today at sales@cloudifyops.com.