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Buying more capacity than the workload needs, then paying for the gap forever.
Quick Definition
Overprovisioning is allocating more cloud capacity than a workload actually needs, oversized instances or excessive resource requests. Often done 'to be safe,' it is a leading cause of cloud waste, and rightsizing directly targets the gap between provisioned and used resources.
Overprovisioning is allocating more compute, memory, or storage than a workload actually uses. It is the cloud's most universal waste pattern, born from reasonable instincts: engineers size for imagined peaks, copy generous defaults, and never look back, because too big never pages anyone while too small does.
The result is structural: industry studies repeatedly find average utilization far below capacity, meaning a large share of every cloud bill purchases headroom that is never touched. In Kubernetes the pattern repeats at the pod level, where inflated resource requests reserve capacity invisibly across the whole cluster.
Example. A service requests 4 CPU cores per replica and uses 0.4 at peak. Across 30 replicas, that is over 100 cores reserved and billed for protection nobody measured. Rightsizing the request frees most of it within a week.
The cure is data over instinct: rightsizing from real utilization, autoscaling to absorb genuine peaks, and a culture where claiming capacity has visible cost. Opslyft's Cost Control surfaces these gaps automatically, and the optimization strategies guide covers the cleanup.
Asymmetric pain: undersizing causes incidents, oversizing causes silent bills. Without utilization data in view, everyone errs large.
Enough for normal spikes plus autoscaler reaction time, often 20 to 40 percent above typical peak rather than multiples of it.
Briefly, for launches and unknown workloads. The discipline is revisiting with real data within weeks, not years.