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Every Atlassian migration plan starts with the same question — what moves? The more useful question, and the one that decides how long it takes, is what doesn't. A Server or Data Center instance that has been running for years is carrying configuration nobody remembers creating, for teams that no longer exist, wired to systems that were switched off.
You can move all of it. It will work. It will also cost you the effort of migrating things you were about to delete, and it will land you in Cloud with the same mess in a more expensive place.
The argument for cleaning up after the move is that it gets you live sooner. In practice it rarely happens — once the instance is live and people are working in it, the appetite for touching workflows disappears, and the cleanup becomes a backlog item nobody picks up.
Cleaning up first also shrinks the thing being tested. Every workflow, custom field and app you retire before the migration is one less item in the validation pass, and validation is where migration timelines actually go.
Custom fields accumulate faster than anything else and are the single biggest driver of a slow, confusing Cloud instance. Look for fields with no values in the last year, fields duplicated across projects because two teams each made their own, and fields attached to screens nobody uses.
The test is not "is this field used" but "would anyone notice if it were gone". Those are different questions and the second one is answerable.
Most long-lived instances have workflows that differ from each other in ways nobody can explain. Before migrating, find the workflows that are genuinely distinct and the ones that are near-copies, and consolidate the copies. A status named slightly differently in three workflows is three statuses in Cloud.
Apps are where migrations stall, and the reason is rarely the app itself. It is that some apps have no Cloud equivalent, some have a Cloud version that works differently, and some hold data that does not migrate with the app. Inventory them early and put each in one of three buckets: has a Cloud path, has a replacement, or is being retired.
The apps that hurt are the ones a single team depends on and nobody else knows about. Ask.
Cleanup has a stopping point, and going past it delays the move for no gain.
The line sits where cleanup stops reducing migration effort and starts becoming a separate improvement programme wearing a migration badge.
Each step shrinks what has to be validated after the cutover, which is the part that determines whether the migration feels controlled or feels like an outage.
The instinct on a migration is to move everything because deciding is harder than copying. But a scoped migration is not a compromise — it is the version where the destination is deliberately better than the origin, and it is the only version where the validation pass is finishable.
See how this played out in practice: a legacy Atlassian Server to Cloud migration for a public-sector organisation. If you are planning a move, our Cloud migration work starts with exactly this inventory.
What to retire, what to keep, and where cleanup stops reducing migration effort and becomes a separate improvement programme.
Start with custom fields, near-duplicate workflows and statuses, projects with no recent activity, deactivated users who still own filters and dashboards, unused groups, and the Marketplace app inventory. The useful test for a field or workflow is not whether it is used but whether anyone would notice if it were gone.
Before. Cleaning up after gets you live sooner in theory, but once people are working in the new instance the appetite for changing workflows disappears and the cleanup becomes a backlog item nobody picks up. Cleaning up first also shrinks the validation pass, which is where migration timelines actually go.
Historical issues, anything covered by a compliance or audit retention obligation, and configuration that would need a full redesign to fix. If fixing something properly is a project of its own, migrate it as-is and address it in Cloud rather than during a cutover.
Rarely because of the app itself. Some apps have no Cloud equivalent, some have a Cloud version that behaves differently, and some hold data that does not migrate with the app. The ones that cause trouble are usually depended on by a single team nobody thought to ask.
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