Traffic is stable.
Model architecture hasn’t changed.
Yet costs keep rising month over month.
It’s hard to explain.
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Traffic is stable.
Model architecture hasn’t changed.
Yet costs keep rising month over month.
It’s hard to explain.
Costs often grow due to inefficiencies rather than usage. Excessive logging, oversized instances, or idle resources can inflate costs silently. Autoscaling misconfigurations are also common culprits.
Profile inference workloads and right-size resources. Monitor cost per prediction, not just total spend.Common mistakes include: Overprovisioning for peak traffic, Ignoring idle compute, Not tracking cost metrics.
The takeaway is that cost is a performance metric too.