How a Single Config Change Reduced AWS Costs by 90 Percent

What this episode covers

Episode 55 of The Software Engineering Podcast. Lucas and Luna dive into one of the most dramatic cost-saving stories in cloud engineering: how a team at a mid-sized fintech company reduced their monthly AWS bill from $80,000 to just $8,000 by changing a single configuration parameter. They explore the overlooked power of AWS Compute Optimizer, the difference between provisioned and on-demand capacity, and why most engineers never look at their reserved instance utilization. Lucas explains the specific parameter change—switching from m5.large to t3.medium instances for stateless batch workers—and how it unlocked a 90 percent savings without any code changes. Luna challenges whether this approach works for latency-sensitive workloads, and they discuss the trade-offs between cost and performance. The episode also covers how to set up automated right-sizing recommendations and why cloud cost optimization is as much about organizational culture as it is about tooling. No hype, just a concrete engineering case study that listeners can apply to their own infrastructure. #CloudCostOptimization #AWS #CostReduction #ReservedInstances #ComputeOptimizer #BatchProcessing #FinOps #Infrastructure #DevOps #EngineeringBestPractices #StatelessWorkloads #InstanceTypes #ProvisionedCapacity #OnDemand #Technology #FexingoBusiness #BusinessPodcast #SoftwareEngineering Keep every episode free: buymeacoffee.com/fexingo

PodParley-generated summary based on available episode metadata and transcript content.