GCP committed use discounts (CUDs) discount compute in return for a one or three year commitment, with spend based CUDs applying to a dollar amount of spend and resource based CUDs applying to specific machine resources in a region. To size coverage without stranding spend, commit only to the steady floor of demand that runs reliably through troughs and quiet seasons, leave the variable peak on demand where sustained use discounts still help, rightsize before you commit so you do not lock waste in for the term, and favour shorter terms where the forecast is less certain. Coverage is a risk adjusted decision: the target is high utilization of every commitment, not the highest possible coverage percentage.
Here is how to find the floor, choose the CUD type, and avoid the classic over commitment.
How do GCP committed use discounts work?
You commit for one or three years and receive a discount against on demand. There are two flavours. Spend based CUDs commit to an hourly dollar amount of spend on a service such as Compute Engine and flex across machine types, which suits an evolving fleet. Resource based CUDs commit to a specific quantity of vCPUs and memory of a machine family in a region for a deeper discount, which suits stable, known workloads. On top of both, sustained use discounts apply automatically to on demand usage that runs for much of the month, so uncommitted steady demand is not paying the full rate either. The relationship between the two is covered in spend based versus resource based CUDs.
How do you find the floor to commit to?
Pull hourly compute usage over a representative period, ideally several months that include a quiet season, and find the level that runs reliably every hour. That floor, not the average and not the peak, is the only demand guaranteed to keep a commitment utilized. Commit to the floor and leave everything above it uncommitted.
| Commit to | What happens | Verdict |
|---|---|---|
| The peak | Commitment idles whenever demand dips below peak | Strands spend every quiet hour |
| The average | Commitment idles below average, on demand above | Partial waste plus partial exposure |
| The floor | Commitment is utilized nearly every hour | Captures the discount with little waste |
Sizing to the floor and tracking utilization is the practical discipline; pair it with the targets in commitment coverage targets on GCP and ongoing CUD utilization monitoring.
What stops a CUD from stranding spend?
Three habits. First, rightsize the fleet before committing, because a CUD bought against oversized machines locks that waste in for one or three years. Second, ladder the terms: use one year commitments where the forecast is softer and reserve three year commitments for demand you are confident will persist, so a falling baseline does not leave you over committed for years. Third, monitor utilization continuously and treat a commitment drifting below full use as a signal to investigate, not a sunk cost to ignore. Sized this way, CUDs capture a deep discount while the variable peak stays flexible and still benefits from sustained use discounts.
A worked example
A scaling fintech was about to place a three year resource based CUD at its average daytime compute, which would have idled every night and weekend. Sizing instead to the genuine overnight and weekend floor, after rightsizing an over provisioned service tier first, produced a commitment that ran close to fully utilized around the clock, with the daytime peak left on demand under sustained use discounts and softer growth covered by one year spend based CUDs. The commitment portfolio captured a deep effective discount with no stranded capacity, part of the program that left the company 41 percent lighter on cloud spend. Figures are verified against billing data and anonymised.
Frequently asked questions
Size your GCP commitments to a forecast you can defend
We help enterprises size and manage CUD portfolios to the steady floor, with high utilization and no stranded spend, as an independent advisory that takes zero provider commissions and answers only to you. Our guarantee: we reduce your cloud spend or we reimburse our service fee, on a Fixed Fee or a no risk Gainshare basis. Download the GCP CUD kit, read the deeper GCP cost optimization guide, and set targets with commitment coverage targets on GCP.
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