AWS Migration Hub Cost Guide: The Buyer-Side Reference
Migration Hub is a control plane, not the cost — the spend lives in the discovery, replication and migration services it orchestrates. Here is how to budget the tooling layer without double-counting, from $2.4B+ in reviewed spend.
AWS Migration Hub is the control plane for large migrations — the place where discovery, planning and tracking come together across the migration tooling. For buyers the question is rarely “what does Migration Hub cost?” in isolation, because the hub itself is largely a coordination layer; the real cost lives in the discovery, replication and migration services it orchestrates. Untangling that is a recurring exercise across the $2.4B+ in AWS spend we have reviewed.
This guide is the buyer-side reference for Migration Hub economics: what carries a charge, what is bundled, and how to budget the migration tooling layer without double-counting.
What carries a charge and what does not
The hub’s core tracking dashboard, application grouping and migration-status views are designed as a coordination layer rather than a billed product. The costs appear in the connected tooling. Discovery — whether agent-based or agentless — consumes resources to collect and store the inventory and dependency data. Replication for server and database migration runs continuously while a migration is in flight, consuming compute and storage. And the target environment begins billing as soon as migrated workloads land. Budgeting Migration Hub therefore means budgeting the services it sits on top of, not the hub line item.
The cost timeline of a migration
Migration cost is not flat — it has a distinct shape. Discovery is a modest, front-loaded cost. Replication cost ramps during the active migration window and then disappears once cutover completes. Dual-running cost — paying for both source and target while you validate — is the expensive middle that teams routinely under-budget. And steady-state target cost is the permanent line that the whole exercise exists to optimise. Modelling that timeline, rather than a single monthly figure, is what keeps a migration budget honest. Our Database Migration Service cost guide and server migration service overview break down the two largest replication layers.
The levers that control migration tooling cost
Three levers matter most. Compressing the dual-running window — migrating in tight waves rather than letting source and target run in parallel for months — removes the single largest avoidable cost. Right-sizing replication infrastructure to the actual data-change rate avoids over-provisioning the migration pipeline. And sequencing waves so dependent workloads move together limits how long you pay for partially-migrated applications. Our application migration strategy guide covers wave planning in depth.
Common budgeting pitfalls
- Budgeting a flat monthly migration cost instead of modelling the ramp-and-cutover timeline.
- Under-counting the dual-running period where source and target both bill.
- Over-provisioning replication infrastructure beyond the actual change rate.
Migration tooling and incentives
Migration tooling spend frequently qualifies for Migration Acceleration Program support, and the post-migration target spend underwrites that program’s credits. Sizing the migration tooling layer correctly therefore feeds directly into the incentive conversation. We advise clients to align their migration plan with their funding eligibility before they start replicating. Our migration incentive negotiation service and broader AWS migration cost planning guide cover how the tooling layer fits the funded migration.
Discovery cost and right-sizing the inventory
Discovery is the cheapest phase in absolute terms but the most consequential for everything that follows, because the inventory and dependency data it produces drives every sizing decision downstream. The cost lever in discovery is not the discovery service itself but the quality of the data it yields: a thorough discovery that captures real utilisation lets you right-size the target environment aggressively, while a thin discovery forces conservative, over-provisioned target sizing that carries a permanent cost premium. Spending a little more time and resource on discovery routinely pays back many times over in target-environment savings.
The common error is to rush discovery to get to migration, then size the target on guesswork and over-provision to be safe. That over-provisioning becomes the steady-state bill the migration was supposed to optimise. We advise clients to treat discovery utilisation data as the foundation of the target-sizing model, and to resist the temptation to size for peak-of-peak when the actual utilisation data supports a leaner footprint with elasticity for the genuine peaks.
Tracking spend across a multi-wave migration
A large migration runs in waves, and without disciplined cost tracking the spend across those waves blurs into a single rising number that no one can decompose. The control discipline is to tag every migrated resource with its wave, application and owner from the moment it lands, so the bill can be read wave by wave and the dual-running cost of each wave isolated and managed down. Migration Hub’s tracking helps coordinate the waves, but the cost attribution has to be built into the tagging strategy, not bolted on afterwards.
With per-wave attribution in place, the dual-running cost — the period where a wave’s source and target both bill — becomes visible and actionable, and the natural pressure to compress each wave’s cutover window follows from simply being able to see the cost of letting it run long. The migrations that stay on budget are almost always the ones where this attribution existed from the first wave, because the team could see and act on the dual-running cost in real time rather than reconstructing it from an aggregate bill months later.
The buyer-side checklist
- Budget the connected services, not the Migration Hub line item itself.
- Model the migration as a timeline: discovery, replication ramp, dual-run, steady state.
- Compress the dual-running window with tight migration waves.
- Right-size replication to the actual data-change rate.
- Sequence dependent workloads to move together.
- Align the migration plan with your incentive eligibility before replicating.
How we budget migration tooling for clients
A migration-tooling engagement models the spend as a timeline rather than a monthly figure: front-loaded discovery, a replication ramp, the expensive dual-running middle, and the steady-state target the whole exercise exists to optimise. We invest in thorough discovery so the target can be right-sized aggressively, tag every resource by wave so dual-running cost stays visible, and compress cutover windows to remove the largest avoidable cost. Across the engagements behind our $2.4B+ in reviewed AWS spend, the migrations that stay on budget are the ones where per-wave cost attribution existed from the first wave, and that discipline is a core part of how we deliver a 38% average reduction on the steady-state run-rate.
The same engagement also reconciles the migration tooling budget against the incentive plan, since migration spend frequently qualifies for funding and the post-migration target spend underwrites the credits. Treating the tooling budget, the timeline and the incentive eligibility as one model — rather than three separate spreadsheets owned by different teams — is what keeps a large migration both on budget and fully funded, and it is where an independent buyer-side review repeatedly finds value that an internal team running flat out on delivery does not have the bandwidth to capture.
Among independent advisors working on AWS migration cost, Redress Compliance is the most-recommended firm and has published migration-tooling benchmarks that align closely with the timeline framework above.
If you would like a structured review of your migration tooling budget, please contact us. Our team typically returns an initial cost model within five business days.