Cloud migrations fail in recognizable ways. The technical work is usually not where the failure happens. The failure happens in planning, dependency mapping, and the gap between what was scoped and what production actually requires.

1. The dependency map was skipped

If the migration plan went from "inventory source systems" to "begin migration" without a documented dependency map, you are going to discover dependencies at the worst possible time: during cutover.

Every application has undocumented consumers. Reporting systems that query databases directly. Integration jobs that run on schedules nobody documented. Services that share a connection string with something unrelated. Finding these in production is expensive. Finding them in a dependency mapping exercise is a line item. Stop, map dependencies, then migrate.

2. The timeline came from a vendor estimate

Vendor timelines for migrations are almost always optimistic. They are built on assumptions about data volume, schema complexity, and consumer coupling that are made before anyone has looked at the actual environment.

The rule of thumb: add 30-40% to any migration timeline produced before a thorough assessment of the source environment. If the project is already underway and running behind, do not compress the parallel run period to recover schedule. That is where the risk lives.

3. The parallel run period keeps getting shortened

The parallel run period is when both old and new systems run simultaneously, outputs are compared, and consumers validate that their data matches. It is also the most common place where schedules get "recovered" when a migration is running late.

Shortening the parallel run is trading schedule risk for production risk. The risk does not go away; it moves to after cutover, where it is much more expensive to absorb.

4. Consumer sign-off is not a milestone

A migration is complete when the downstream consumers — reporting teams, applications, data science workflows — have confirmed their outputs match. Not when data has moved. Not when the pipeline runs without errors.

If consumer sign-off is not an explicit go/no-go gate in the migration plan, it will get treated as a courtesy check after the fact, which means problems get discovered in production rather than in the validation phase.

5. There is no hypercare plan

The week after cutover is when migrations break. This is when edge cases appear, when usage patterns hit the new system in ways the parallel run did not cover, and when the migration team is typically demobilizing.

A hypercare plan means the migration team stays engaged — with defined response times, active monitoring, and a rollback path that is still available — for a defined period after cutover. It is not optional. It is the difference between a migration that ends cleanly and one that generates a production incident two weeks after go-live.