Choose providers on purpose, and keep the choice reversible.
Decide where workloads and data live across Cloudflare, AWS, Google Cloud, and Azure, with residency, egress, and exit cost accounted for.
Most organizations are already multi-cloud, usually by accumulation rather than design. One provider arrived with an acquisition, another with the data team, a third with the AI workload. The result is a footprint nobody chose and few can price.
This is where leverage disappears. Egress fees make migration theoretical. A residency requirement lands after the architecture is set. Committed spend on one provider quietly determines the next three technical decisions.
Multi-Cloud Placement makes the footprint deliberate. It gives the team a clearer way to decide what runs where based on latency, residency, sovereignty, committed spend, and the real cost of leaving. What matters next is placement that reflects the requirement rather than the history.
Start with the workload that would hurt most to move —
Pick the service with the deepest provider dependency and price what changing it would actually cost.
Write the residency constraints down —
Capture data-location, jurisdiction, and processing requirements before selecting a provider rather than after.
Keep an exit path per workload —
For each significant workload, know the destination, the migration path, and the order of magnitude of the cost.
Outcomes
Deliberate provider mix —
Each workload sits with a provider chosen for a stated reason rather than inherited from an earlier decision.
Residency requirements met —
Data location and processing jurisdiction are satisfied by design and can be demonstrated on request.
Preserved negotiating position —
Exit cost is known per workload, which keeps commercial leverage real at renewal.