· Cloud · 2 min read
Cloud migration cost modeling before the move
How to estimate costs early enough to steer architecture decisions.
Cloud migration cost modeling should happen before architecture decisions are locked. If you wait until the end, you lose the ability to steer. A basic model is usually enough to compare options and avoid expensive surprises.
Build a baseline by exporting current billing data and mapping it to workloads. Identify the top cost drivers and whether they scale with traffic, data volume, or time. Track both average and peak usage. Many migrations fail to account for peak sizing, which can double the estimate.
Translate to the target environment
Map current services to equivalents in the target cloud and estimate unit costs. Include compute, storage, data transfer, and managed service pricing. Add a buffer for unknowns and expected growth. Document assumptions so the model can be updated when new data appears.
One time costs matter. Include migration effort, tooling, and the cost of running two environments in parallel during validation. Parallel run time is often the largest hidden cost and should be listed explicitly. If there are licensing changes, include those as well.
Present the model clearly
Use a simple table with current cost, target cost, and one time cost. Add a short notes section that lists assumptions and risk factors. This makes it easier for stakeholders to approve the plan and for engineers to choose cost aware designs.
Review the model at key milestones. Update it after the inventory phase, after the first migration wave, and before final cutover. This keeps it realistic and makes it a useful decision tool.
A cost model does not need to be perfect. It needs to be transparent enough to guide decisions while the design is still flexible.
Look for cost drivers hidden in data transfer. Cross region replication, analytics exports, and logging can add large, recurring fees. If you model only compute and storage, your estimate will be optimistic.
Use conservative assumptions for capacity and growth. If you expect 20 percent growth, model 30 percent. Migration projects often grow in scope and timeline, so a conservative model helps prevent later budget shocks.
Tie cost decisions to architecture choices. If a managed database is too expensive, propose alternatives and document the trade offs. A cost model is most useful when it informs design, not when it only reports numbers.
