Every morning, without fail, API response times double or triple for a predictable window. Most engineering teams treat this as a scaling problem and throw more instances at it. But the real culprit is almost never raw traffic volume — it's a collision between your cron jobs, your cache expiry, and your customers' usage patterns. In this episode, Lucas and Luna walk through a real-world case where a SaaS platform's latency chart looked like the Matterhorn at 10:05 AM. They trace the root cause to a database connection pool exhausted by a scheduled report generator, and a Redis cache that evicted hot keys right as the morning cohort clocked in. The fix: staggering cron by a few seconds and pinning five critical keys. Listeners walk away with a diagnostic framework they can apply to their own dashboards tomorrow.

#Latency #APIPerformance #CronJob #CacheEviction #Redis #DatabaseConnectionPool #SaaS #Scaling #Diagnostics #Engineering #DeveloperTools #Infrastructure #Observability #BusinessAndTechnology #FexingoBusiness #BusinessPodcast #API #PerformanceTuning

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