How Much CUD Should You Buy?

Every Google Cloud committed use discount decision lives between two mistakes. Commit too much and you pay the discounted rate for capacity you never use. Commit too little and the demand you were sure about keeps running at the full on-demand rate. Three numbers tell you where you are between those two.

Coverage: are you leaving discount money on the table?

Coverage is the share of your demand met by commitments rather than on-demand. If a steady chunk of demand is running uncommitted month after month, your coverage is low and you're overpaying — that demand is a candidate for a commitment. Coverage going up is usually good, right up until it starts hurting utilization.

Utilization: are you paying for idle capacity?

Utilization is the flip side: the share of your committed capacity that's actually used. If you commit to 100 units but only ever use 70, your utilization is 70% and you're paying the discounted rate for 30 units of nothing. High coverage with low utilization is the classic over-commitment trap — it looks efficient until you notice the idle capacity.

The sweet spot maximizes coverage of demand you'll actually use while keeping utilization high. Those two goals pull against each other, which is why “just commit more” and “just commit less” are both wrong.

Break-even: is a given commitment worth it?

Break-even is how long a commitment must stay utilized before it costs less than paying on-demand for the same usage. A commitment charged at a discounted monthly rate for its full term only pays off if the underlying demand sticks around past that point. Demand likely to churn before break-even shouldn't be committed — or should take a shorter term with a nearer break-even.

Putting the three together

For one flat slice of demand, you can reason about these by hand. For a real portfolio — many contracts, staggered end dates, existing commitments, demand that tapers as contracts lapse — coverage, utilization, and break-even interact across every month at once, and the cost-optimal answer isn't obvious. That's the job of the Solvicus CUD optimizer: it computes the commitment plan that minimizes total spend, and shows you the coverage, utilization, and savings behind every purchase so you can see — and change — exactly why it recommends what it does.