FinOps Patterns for Kubernetes in Production Running Kubernetes on AWS doesn't automatically mean running it efficiently. Most teams focus on stability and delivery and discover their cloud bill three months later, when the damage is done. In this talk, I share concrete lessons from optimizing EKS infrastructure costs in production: what to measure, where the waste actually hides, and which levers move the needle, without breaking anything. We'll cover: 1. Why standard cloud cost tools (Cost Explorer, Kubecost) only give you half the picture. The underestimated impact of Karpenter, instance diversification, and Spot strategy on real workloads. 2. How right-sizing Kubernetes requests saved more than any Reserved Instance commitment. 3. The FinOps discipline that stuck vs. the optimizations that quietly regressed No vendor pitch. No theoretical framework. Just patterns, numbers, and honest trade-offs from the field including a -20% reduction on a production EKS cluster. You'll leave with a checklist you can apply to your own cluster next week.
Rodrigue NDE is a Cloud Platform Engineer with 7 years of experience, specializing in Kubernetes, AWS infrastructure, and FinOps. He has led the design and industrialization of production-grade EKS platforms for multiple organizations, with a focus on reliability, security, and cost efficiency. His background as a Java Tech Lead before moving into Cloud Engineering gives him an unusual perspective: he builds platforms with the developer experience in mind, not just the infrastructure metrics. Recent highlights include a 20% reduction in AWS costs on an EKS production cluster, a platform SLA improvement to 99.9%. Rodrigue is currently working toward his next role as a Senior Platform Engineer, with a particular interest in FinOps, Kubernetes security, and platform self-service.
