Running Kubernetes in the cloud brings flexibility, scalability, and high availability. However, without proper configuration, it can lead to unexpected costs and resource waste. Amazon Elastic Kubernetes Service (EKS) makes it easy to deploy a Kubernetes cluster on AWS, but without a FinOps approach, its operation can be inefficient.
In this article, we explore how to combine the benefits of Kubernetes and FinOps to reduce costs while maintaining performance and reliability.
Key Reasons to Optimize EKS Operations
FinOps in a Kubernetes environment means:
- Cost transparency at the level of teams, projects, or environments (e.g., dev, test, prod)
- Efficient use of computing resources—no overprovisioned nodes or idle workloads
- Process automation such as scaling, resource cleanup, and cost monitoring
- Better budget control without limiting development velocity
Common Mistakes in Running Kubernetes on AWS
| Feature | Consequence |
|---|---|
|
Unoptimized node groups
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Powerful (and expensive) instances are only partially utilized
|
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Missing autoscaling
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Kubernetes nodes run constantly, even when not needed
|
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Neglected environment cleanup
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Test namespaces and data volumes remain active for months
|
|
CloudWatch logs without retention rules
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Costs increase with the volume of historical logs
|
|
On-demand instances only
|
Spot instances could significantly reduce costs
|
Recommended FinOps Practices for EKS
Automatic Performance Scaling
By enabling the Cluster Autoscaler, the number of nodes adjusts to current demands. Without proper scaling conditions, EKS runs at max capacity—unnecessarily.
TIP: Also implement HPA (Horizontal Pod Autoscaler) to adjust the number of pods based on load.
Combining Spot and On-Demand Instances
Spot instances can be up to 90% cheaper than on-demand. EKS supports mixed node groups where Kubernetes prioritizes spot instances and falls back to on-demand when needed.
Ideal for:
- Staging environments where downtime is acceptable
- Restartable batch jobs
Automated Resource Cleanup
Using scripts, cron-jobs, or tools like Kubecost, you can identify:
- Forgotten namespaces and volumes
- Unused load balancers and PVCs (PersistentVolumeClaims)
- Excess logs and debug containers
TIP: Regular cleanup should be part of your CI/CD pipeline or scheduled cluster jobs.
Cost Monitoring
Monitoring is as essential to FinOps as optimization itself. In EKS, we recommend:
- Viewing costs by namespace, labels, or teams (e.g., via Kubecost or AWS Cost Explorer)
- Creating a Grafana dashboard linked to Prometheus
- Using AWS Budgets to set limits and notifications
Case Study: 34% Monthly Savings Thanks to FinOps
A customer operated several EKS clusters for development, testing, and production. After implementing FinOps principles:
- Reduced the size of some node groups and enabled autoscaling
- Introduced spot instances in dev environments
- Deleted hundreds of unused PVCs and ELBs after test deployments
- Shortened CloudWatch log retention from 30 to 7 days
Result? A 34% monthly reduction in EKS costs.
Conclusion: Kubernetes and FinOps Belong Together
Optimizing Kubernetes operations on AWS is not a one-time task. It requires a systematic approach, cost visibility, and automation:
- Implement autoscaling and properly size node groups
- Combine on-demand and spot instances
- Regularly monitor and clean up resources
- Use tools for cost tracking and alerting
A FinOps approach helps you keep costs under control—without limiting innovation or development cycles.
Want to know how to optimize Kubernetes in your cloud environment? Get in touch—we’re happy to help.
