Commitment coverage is the share of your usage paid for through a discounted commitment rather than on demand. The instinct is to maximise it, because the discount on AWS Savings Plans and Reserved Instances runs from roughly 20 to 72 percent against on demand. The discipline is to cover only the usage you are confident will still be there for the full term, because a commitment you do not use is worse than the on demand you avoided. The buyer takeaway: set the target from a defensible baseline of stable usage, typically leaving coverage at the predictable floor and a deliberate buffer below your recent low, and let the variable portion ride on demand.
Here is how to find that floor, set the target, and stage commitments so you never strand spend.
Why is 100 percent coverage the wrong target?
A commitment is a bet that future usage will at least match what you locked in. Cover 100 percent of today's usage and any decommission, migration, or efficiency win leaves you paying for capacity you no longer run, at the committed rate, for one or three years. The effective saving on a commitment is the discount minus the waste from hours you committed to but did not use. Push coverage too high and the waste term eats the discount. The objective is the highest effective savings rate, not the highest coverage percentage, and those are not the same number.
How do you find the stable floor?
Look at hourly usage over a representative period, ideally several months that include your normal peaks and troughs. The floor is the level your usage rarely drops below, the baseline that runs whether traffic is high or low. That floor is the safe coverage target, because committing to it carries little risk of under use. Sit the commitment a deliberate margin below the floor if your forecast is uncertain, an expansion is planned, or a workload might move. Everything above the floor is variable demand that belongs on demand or, where the workload tolerates interruption, on spot.
How should you stage and layer commitments?
Do not buy the whole target in one purchase. Layering smaller commitments that start and expire at different times keeps your average term short and your flexibility high, so you can adjust as the forecast firms up. Favour the more flexible instrument for the uncertain layer: Compute Savings Plans flex across instance family, size, and region, while EC2 Instance Savings Plans and standard Reserved Instances trade that flexibility for a deeper discount on a specific commitment. Cover the rock solid base with the deeper discount instruments, and the less certain layer with the flexible ones.
A worked example
A Fortune 500 retailer had pushed Savings Plan coverage near total during a growth phase, then rationalised several workloads and migrated others to Graviton. Coverage that once fit now exceeded actual usage, and the surplus commitment ran as pure waste at the committed rate. Resetting the target to the demonstrated stable floor, layering future purchases on shorter staggered terms, and leaving the variable top on demand lifted the effective savings rate even though the headline coverage number fell. The lesson held: the goal was the best realised saving, not the biggest coverage figure. Figures are verified against billing data and anonymised.
| Usage layer | Cover with | Why |
|---|---|---|
| Stable floor | Reserved Instances or EC2 Instance Savings Plans | Deepest discount, lowest risk |
| Likely but uncertain | Compute Savings Plans | Flexibility to adjust |
| Variable peak | On demand or spot | No lock in on volatile demand |
Talk it through with us
If your coverage was set during a different growth phase, it is probably mismatched to today's usage, and resetting it to the real floor is where the saving is. We take zero provider commissions and answer only to you, across AWS, Azure, GCP, and OCI. Our guarantee is plain: we reduce your cloud spend or we reimburse our service fee, on either a Fixed Fee scoped up front or a no risk Gainshare share of verified savings. Book a strategy call to scope it for your estate, and follow more analysis in The Cloud Spend Navigator.
Frequently asked questions
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How do you set the coverage target safely?
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