Cloud cost drift

See how an assumed monthly change compounds across 12 months, then compare the scenario with your billing data.

The decision

Which cost change deserves investigation before it becomes the new baseline?

Assumptions and limits

A scenario is not a forecast. It excludes price changes, commitments, traffic mix, credits, and tax. Use billing exports to validate the growth rate.

Describe your situation

Current monthly cloud spend (USD)

Use a recent, representative invoice total. Do not include a target or list price.

Assumed monthly spend change (%)

Use an observed month-over-month trend or a scenario you want to test. Negative values model a decline.

How this tool works

Month n spend = current monthly spend × (1 + monthly change / 100) to the power n, for months 1 through 12. Month 1 already includes one monthly change.

Add those 12 monthly amounts for the annual scenario. Subtract 12 × current monthly spend to compare it with flat spend. A difference is not an identified saving or waste.

Model assumptions

  • A scenario is not a forecast. It excludes price changes, commitments, traffic mix, credits, and tax. Use billing exports to validate the growth rate.
  • The same percentage change is applied at the end of each month for 12 months. Values are rounded only for display.

Hypothetical worked example

These illustrative inputs are not your result, a customer case, or a benchmark. Change the inputs above to review your own situation.

Current monthly cloud spend (USD)
10000
Assumed monthly spend change (%)
1

Growth compounds across the year

At a constant 1% month-over-month change, the entered monthly spend produces the following 12-month scenario. This does not identify waste or savings.

Month 12 spend
$11,268.25
12-month total
$128,093.28
Difference from flat spend
+$8,093.28
  • The difference is entirely driven by your assumed monthly change. No efficiency or discount factor is applied.

Checks for this example

  • Compare the last six months of actual billed spend with usage and unit-cost trends.
  • Separate commitments, credits, data transfer, idle resources, and traffic changes before naming a root cause.