How One Engineer Cut Logging Costs 90 Percent Without Losing Observability

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How One Engineer Cut Logging Costs 90 Percent Without Losing Observability

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Episode 80 of The Software Engineering Podcast dives into a specific cost-optimization story: how a senior engineer at a mid-size fintech company reduced their cloud logging bill by 90 percent — from $80,000 per month to under $8,000 — without sacrificing the signal their on-call team relied on. Lucas and Luna walk through the technical decisions: switching from structured JSON logging to a custom binary format with protobuf, implementing a two-tier retention policy that kept high-cardinality metrics hot for only 24 hours, and writing a smart sampling layer that preserved 100 percent of error traces while dropping 95 percent of repetitive success logs. They discuss the trade-offs — longer query times on cold storage, the learning curve for the team, and the initial pushback from developers used to grep-friendly logs. The episode ends with a practical framework any team can adapt: measure your log volume per service, identify the noisiest sources, and ask whether every field in every log line earns its storage cost. #SoftwareEngineering #CloudCosts #Observability #Logging #Fintech #Protobuf #BinaryFormat #Sampling #RetentionPolicy #CostOptimization #EngineeringPodcast #FexingoBusiness #BusinessPodcast #Technology #LogManagement #Scalability #DevOps #SiteReliability Keep every episode free: buymeacoffee.com/fexingo

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