Use case
Optimizing Kubernetes Costs with Kubecost and Karpenter on AWS EKS
- Mayur Duduka
About the Customer
Virora, a leading organization in the Hospitality & Guest Experience sector, operates in a fast-paced environment requiring agile and cost-effective IT solutions. With a mission to innovate and deliver value, they maintain a robust cloud infrastructure to support their applications, development, and scaling needs.
Customer Challenge
The organization was facing escalating costs associated with running their workloads on Amazon Elastic Kubernetes Service (EKS). The primary challenge was to optimize resource allocation and reduce costs without compromising application performance and reliability. Instances in their Kubernetes cluster were either underutilized or oversized, leading to inefficiencies. A lack of detailed cost visibility further complicated their ability to address these issues effectively. If left unresolved, these inefficiencies could strain the IT budget, limit scalability, and impact the company’s ability to invest in new initiatives.
Solution
The customer engaged [Partner Name] to implement a solution leveraging Kubecost, Karpenter, and AWS-native tools for cost and resource optimization.
1) Kubecost Implementation:
Kubecost was installed and integrated with the existing AWS EKS cluster using Helm. This allowed for real-time monitoring and detailed insights into the cluster’s resource utilization and associated costs. Prometheus and Grafana were also integrated to provide enhanced visualization of cost data, enabling teams to make data-driven decisions.
2) Dynamic Scaling with Karpenter:
Karpenter, AWS’s open-source Kubernetes cluster autoscaler, was deployed to dynamically provision and scale nodes based on workload demands. The use of Spot Instances with Karpenter significantly reduced the cost of running workloads while maintaining performance levels.
3) Resource Requests and Limits:
Requests and limits for Kubernetes resources were configured to align with application needs. This step ensured that workloads utilized just the right amount of resources, eliminating waste and minimizing the risk of over-allocation.
4) Additional Cost Optimization Strategies:
AWS Trusted Advisor was employed to identify opportunities for further cost savings. Cost management practices, such as implementing schedules for non-production environments and decommissioning unused resources, were also introduced.
Results & Benefits
The implementation resulted in significant cost savings and improved resource utilization:
- Cost Reduction: Reduced overall Kubernetes costs by 30% through the combination of Karpenter with Spot Instances and Kubecost optimization insights.
- Improved Visibility: Teams gained real-time insights into resource usage and costs, enabling better financial accountability and planning.
- Operational Efficiency: Automated scaling with Karpenter eliminated manual intervention, reducing management overhead.
- Enhanced Decision-Making: The integration of Kubecost with Grafana provided actionable insights, helping stakeholders make informed decisions.
About IAMOPS
IAMOPS is a full DevOps suite company that supports technology companies to achieve intense production readiness.
Our mission is to ensure that our clients’ infrastructure and CI/CD pipelines are scalable, mitigate failure points, optimize performance, ensure uptime, and minimize costs.
Our DevOps suite includes DevOps Core, NOC 24/7, FinOps, QA Automation, and DevSecOps to accelerate overall exponential growth.
As an AWS Advanced Tier Partner and Reseller, we focus on two key pillars: Professionalism by adhering to best practices and utilizing advanced technologies, Customer Experience with responsiveness, availability, clear project management, and transparency to provide an exceptional experience for our clients.
