The Autoscaling Bug That Costs Companies Thousands Before Anyone Notices

Short summary

Autoscaling frequently produces higher costs than fixed capacity through configuration patterns teams only discover during billing audits. 'Thrashing' occurs when scale-up/down cycles respond to traffic spikes shorter than provisioning time, combined with metric mismatches (scaling on CPU when memory is the constraint) and conservative scale-down delays. Treating min/max boundaries and scaling thresholds as quarterly-reviewed metrics prevents accumulating waste.

• •Autoscaling thrashing—rapid scale-up/down cycles—generates wasted capacity when triggered by short-duration traffic spikes
• •Metric mismatches: scaling on CPU utilization when app is actually memory-bound or I/O-bound
• •Quarterly review of min/max boundaries and scale-down cooldowns prevents cost creep from asymmetric default behavior

Generated with AI, which can make mistakes.