How API Logging Pipelines Ingest the Wrong Data

Episode 58 of The Developer Tools Podcast explores a subtle but costly failure in API observability: when your logging pipeline is configured to capture the wrong fields, you end up with petabytes of noise and zero signal. Lucas and Luna dissect a real-world case from a mid-stage payments company that was logging entire request and response bodies for every API call, burning through $40,000 a month in data ingestion costs while missing critical latency outliers. They walk through how structured logging with selective field capture, sampling strategies, and log-level tuning can cut costs by 80% without sacrificing debuggability. Along the way, they touch on the tension between engineers who want 'all the data just in case' and platform teams who have to manage the bill. A practical, sobering look at why more logs aren't better logs. #API #Observability #Logging #DataIngestion #CostOptimization #StructuredLogging #SamplingStrategies #LatencyMonitoring #DeveloperTools #DevOps #EngineeringDecisions #Business #Technology #FexingoBusiness #BusinessPodcast #DeveloperToolsPodcast #SoftwareEngineering #APIInfrastructure Keep every episode free: buymeacoffee.com/fexingo