Cut Your Kubernetes Costs by 30-50% in Just 45 Days

The Challenge

A web intelligence company running 7,000+ pods on Amazon EKS was facing rapidly escalating compute costs. Their Cluster Autoscaler was over-provisioning nodes, and their primary webscraping application—the core revenue driver—was requesting far more CPU and memory than it actually needed.

The Approach

I executed a three-pronged optimization strategy focused on the infrastructure layer—no application code changes required:

• Karpenter Migration: I replaced Cluster Autoscaler with Karpenter, enabling smarter bin-packing and access to a diverse pool of instance types. Karpenter's just-in-time provisioning eliminated CA's excess reserve capacity.
• Pod Right-Sizing: Using Grafana dashboards to analyze actual resource utilization, I identified that the primary webscraping application was requesting 3-4x more resources than peak usage. I tuned resource requests and limits to match real-world consumption.
• Instance Diversification: I configured Karpenter NodePools to select from 20+ instance types, enabling the system to provision the most cost-effective option for each workload's actual requirements.

The Implementation

I rolled out the optimizations incrementally over several weeks, carefully monitoring each change to ensure zero downtime. I tracked cost savings in real-time, validating that each optimization delivered the expected impact before moving to the next phase. This methodical approach gave stakeholders complete confidence in the migration while delivering immediate, measurable results.