On-Prem to Cloud Migration Cost: What to Budget in 2026
On-Prem to Cloud Migration Cost: What to Budget in 2026 ! Engineers reviewing cloud migration cost estimates Moving from on-premises infrastructure to the cloud costs anywhere from tens of thousands of dollars to multiple millions, depending on what you move and how.
Moving from on-premises infrastructure to the cloud costs anywhere from tens of thousands of dollars to multiple millions, depending on what you move and how. Industry guidance puts small workload migrations at roughly $20,000 to $100,000, with enterprise programs reaching multi-million dollar figures once labor, compliance and integration are counted. The sticker price of the cloud is rarely the problem. The problem is the budget line nobody drew: the double-run period, the data work, the training and the tuning that follows.
This guide splits the bill into one-time migration costs and recurring cloud costs, shows what moves the total, compares it against on-prem total cost of ownership (TCO), and ends with how to estimate ROI and trim the spend. Every figure below is a range or an illustration, not a quote. Your numbers will depend on your estate.
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TL;DR
- Separate project costs (assessment, migration labor, double-running, training) from run costs (compute, storage, networking, licensing, support). Finance will ask for this split.
- Small workloads often land between $20,000 and $100,000; enterprise programs run far higher. Treat any single “average” with suspicion.
- The costs that surprise teams are the parallel on-prem and cloud overlap, integration work, and idle or oversized resources after cutover.
- Savings usually show up only after workloads stabilize, so build the ROI model over 3 to 5 years, not 3 months.
- Right-size, migrate in priority order, and run an optimization pass after go-live. That is where most of the recoverable money sits.
Table of Contents
- Why migration budgets miss the mark
- One-time migration costs
- Recurring cloud costs
- What moves your total
- On-prem TCO vs. cloud: compare like with like
- How to estimate ROI
- Hidden expenses to catch early
- How to reduce the cost
- Our perspective
- Plan your migration with Bitrupt
- FAQ
- Sources
Why migration budgets miss the mark
Most teams price compute and storage, because those are the line items a cloud calculator shows. The real drivers are often the temporary double-run period and the labor-heavy integration and data migration work that continues after the initial cutover.
Analogy: budgeting a cloud migration from a compute calculator is like budgeting a house move from the truck rental. The truck matters. So do the packing, the overlapping rent, the repairs at the new place and the furniture that does not fit.
A second trap is the calculator itself. FinOps practitioners warn that standard calculators fail to capture workload-specific dependencies and the “bubble cost” of running both environments in parallel. Use calculators for the run-rate. Use a real assessment for everything else.
One-time migration costs
These are the project costs: temporary, lumpy and the easiest to under-scope.
Assessment and planning
You inventory servers, applications, databases, dependencies, licenses and data volumes. You then decide a path for each workload: retire, rehost, replatform, refactor or replace. Discovery tools reduce the effort. AWS offers Migration Evaluator, a complimentary service for building data-driven assessments and business cases, and Google Cloud’s Migration Center includes cost estimation that generates quick offline estimates for running workloads in Google Cloud. The tools are free or cheap. The analysis of what they output is the paid part.
Application migration
This is usually the largest line. A rehost (lift-and-shift) is the cheapest per workload and the fastest. A replatform swaps components, for example moving a self-managed database to a managed one. A refactor rewrites parts of the application to use cloud-native services and costs the most engineering time. Each step up buys lower run costs or better scalability, at a higher project price.
Data transfer
Bringing data in is generally the cheap direction. AWS, for instance, does not charge for data flowing into it, though you still pay for the bandwidth you use, any dedicated connection, and the engineering hours for validation and cutover sync. Large archives may call for physical transfer appliances, which carry their own fees. Plan the sync window carefully: the longer source and target stay in sync, the longer you double-pay.
Infrastructure setup
Accounts, networking, identity, landing zones, logging, backup and CI/CD pipelines all need building before the first workload lands. Codifying this saves rework; our overview of infrastructure as code tools covers the options.
Security and compliance
Expect work on identity and access, encryption, key management, network segmentation, monitoring and audit evidence. In healthcare and finance, compliance mapping can rival the technical migration in effort. Budget for it explicitly rather than hoping it fits inside “setup.”
Testing and validation
Functional, performance, security and failover testing, plus a rehearsed rollback. Skipping this is the classic false economy: a failed cutover costs more than the test cycle you saved.
Staff training and external expertise
Your team has run racks and hypervisors for years. Cloud operations is a different discipline. One anecdote circulating in the ranking guides describes a healthcare provider that budgeted $1.2M for a migration but set aside only $100K for training and outside expertise. Whatever the exact case, the lesson holds: training is a line item, not a favor.
Downtime and double-running
Every hour of planned downtime has a business cost, and every month of overlap means paying for data center and cloud at once. A two-month overlap on a mid-size estate can easily cost five figures, which is why cutover planning belongs in the budget meeting, not just the runbook.
Recurring cloud costs
These are the run costs that replace your hardware refresh cycle.
| Run cost | What drives it | Where it hides |
|---|---|---|
| Compute | Instance size, hours, pricing model (on-demand, reserved, savings plans) | Oversized VMs, idle dev environments, GPU capacity held for low traffic |
| Storage | Volume, tier, snapshots, retention | Orphaned disks, old snapshots, duplicate backups |
| Networking | Traffic out to the internet, between zones and regions, dedicated links | Chatty microservices across availability zones, egress to your own office or another cloud |
| Licensing | Bring-your-own vs. license-included OS and database | Per-core database licensing that scales with instance size |
| Support | Provider support tier, usually tied to spend | Premium tiers bought and never used |
| Maintenance and operations | Patching, monitoring, on-call, cost governance | People time that used to sit in the data center budget |
One risk deserves a flag. Over-committing to savings plans or reservations can cause severe financial loss if usage does not stabilize, and AI workloads often carry idle allocated capacity: you pay for premium GPU blocks whether or not traffic arrives. Provisioned AI capacity, for example, is bought for a fixed term and paid for around the clock.
What moves your total
Five factors explain most of the spread between a $40,000 migration and a $4 million one.
- Workload size. Number of servers, applications and environments (production, staging, DR).
- Data volume. Terabytes mean longer sync, more validation and, later, more storage and possible egress.
- Application complexity. A documented web app on a standard database is a different job from a 15-year-old system with hard-coded IPs and undocumented batch jobs.
- Downtime tolerance. Near-zero downtime needs replication, parallel running and rehearsals. A weekend maintenance window costs far less.
- Migration strategy. Rehost is quick and cheap upfront, but can leave you paying for oversized, unoptimized instances. Refactor costs more now and often less every month after.
An illustration, not a quote
Take a hypothetical mid-size company: 60 servers, 40 TB of data, a mix of standard apps and two legacy systems. A phased plan might look like this in structure:
- Assessment and planning: a few weeks of senior time.
- 40 servers rehosted, 15 replatformed, 5 retired.
- Two legacy systems left for a later refactor phase.
- A two-month overlap of on-prem and cloud for the first wave.
Price each of those with real quotes and you have a defensible number. Price them with a single “cost per server” figure from a blog and you have a guess. Your own total will differ, sometimes a lot.
On-prem TCO vs. cloud: compare like with like
On-prem is largely a capital model. It hides costs such as power, cooling and hardware refresh cycles, while cloud is consumption-based operating spend. To compare fairly, count every cost on both sides.
On-prem TCO includes:
- Servers, storage and network gear, amortized over their refresh cycle
- Data center space, power and cooling
- Software licenses and maintenance contracts
- Staff time for racking, patching, backups and DR testing
- Capacity bought ahead of demand and left idle
Cloud TCO includes:
- Everything in the run-cost table above
- Amortized one-time migration costs
- Cloud operations and governance staff or partners
- Any on-prem assets you keep (a hybrid remainder is common)
If you want a primer on what counts as on-premise infrastructure before you build the model, this explainer on on-premise versus cloud data is a clear starting point.
Expect honesty from the numbers. Many organizations assume immediate savings, but efficiency gains usually appear only after workloads stabilize and migration overhead is gone. For steady, predictable workloads on fully depreciated hardware, on-prem can still be cheaper. The cloud wins on elasticity, speed to launch, resilience and avoided refresh spending.
How to estimate ROI
- Baseline on-prem for 3 to 5 years, including the refresh you would otherwise face.
- Split project costs from run costs. Separating temporary, volatile expenses like double-runs and consultants from steady-state operations keeps the business case defensible when Finance reviews spend drift.
- Model the run-rate after optimization, not at the first invoice. First-quarter bills run high.
- Add non-cash value carefully: faster releases, fewer outages, avoided downtime. Put a number on it only where you can defend it. FinOps guidance on resilience shows how to weigh infrastructure cost against total economic exposure, for example whether a multi-zone design pays for itself.
- Run what-if scenarios. Compare rehost against replatform for your top five workloads, and note the break-even month for each.
Can migration costs be capitalized?
Possibly. Under FASB ASU 2018-15, certain implementation costs of a cloud computing arrangement that is a service contract may be capitalized, aligning them with internal-use software and amortizing them over the hosting term. Which of your costs qualify is a judgment for your controller and auditors, so take your specific project to your CPA before you book anything.
Hidden expenses to catch early
- Double-running. Plan the shortest safe overlap and put an end date on the old environment.
- Idle capacity. Dev and test environments running nights and weekends, and reserved capacity that nobody uses.
- Over-commitment. One FinOps case study on a post-migration cost increase concluded the team should have left a portion of its VM fleet uncovered by commitments during migration while sizes were still changing. Buy commitments after workloads settle.
- Egress and cross-zone traffic. Architecture decisions show up later as network bills.
- Licensing surprises. Check how your database and OS licenses transfer.
- Integration debt. Connections to ERP, payment, identity and partner systems take longer than the servers do. Our post on hidden cloud ERP costs shows how to budget the buckets teams forget.
- Replication bills. Tooling choice matters; see our rundown of cloud migration tools.
How to reduce the cost
Right-size before and after
On-prem servers are usually sized for peak plus growth. Moving them one to one imports that waste. Use actual utilization data to pick instance sizes. Providers are building this into tooling: Google Cloud’s FinOps Hub 2.0 uses Gemini Cloud Assist to flag underused resources such as VMs running near 5% capacity.
Prioritize workloads
Start with workloads that are easy to move and expensive to keep: aging hardware, expiring support contracts, spiky demand. Retire what nobody uses. Leave the tangled legacy system for a later wave when your team has practice.
Optimize after go-live
Schedule a review at 30, 90 and 180 days. Autoscaling, storage tiering, containerizing parts of the stack and cleaning up orphaned resources all happen after cutover. Practitioners describe a maturity path from manual, conservative purchasing toward data-driven automation and systematic monitoring. Our write-up of a three-phase AWS cost optimization shows how engineering and finance can work through it over 6 to 12 weeks.
Our perspective
We see the same pattern again and again. A team treats migration as a one-time purchase, signs off a number built from compute and storage, then spends the next year explaining the variance. The fix is rarely a better calculator. It is a better assessment and a team that stays close to the workload after cutover.
This is why we staff engagements with senior engineers only. The costly mistakes in migration, such as choosing rehost for a workload that should be replatformed, or committing to reservations too early, are judgment calls. They are made in the first few weeks, and they echo for years in the monthly bill. We also keep response times fast and give you direct access to the technical decision makers, because a migration with a two-week lag on every question runs long, and long means double-running.
Our advice: ask every vendor, including us, to show project costs and run costs as separate numbers, with the assumptions written down. If they cannot, the estimate is not finished.
— Usama
Plan your migration with Bitrupt
If you are weighing a move, our cloud migration services cover assessment, migration, cloud and DevOps setup and ongoing support, delivered by senior engineers. We also offer flexible models such as development pods and staff augmentation, so you can add capacity to your own team rather than hand over the whole project. Pricing is negotiated per project, so we do not publish rates. Tell us about your environment and we will scope it with you.
FAQ
What is the average cost of a cloud migration project?
There is no reliable single average. Industry guidance suggests small workloads often run $20,000 to $100,000, while enterprise programs reach millions. Your figure depends on workload count, data volume, complexity, downtime tolerance and strategy, so get an assessment-based estimate.
How do I migrate data from on-prem to the cloud?
Inventory and classify the data, choose a transfer method (network transfer, dedicated link or physical appliance), then run an initial bulk copy, ongoing sync and a validated cutover. Test restores and keep a rollback path. The longer the sync period, the more you pay for running both environments.
Will the cloud always be cheaper than on-prem?
No. Steady, predictable workloads on hardware you already own can cost less on-prem. The cloud tends to win where demand varies, where hardware refreshes are due, or where speed and resilience carry real business value. Compare full TCO on both sides before deciding.
Can data migration costs be capitalized?
Some implementation costs for cloud service contracts may be capitalized under ASU 2018-15, then amortized over the hosting term. Eligibility depends on the specific costs and contract, so confirm with your accountant or auditor.
Sources
- Cloud Migration Costs: Savings, Benefits & Enterprise Cost Guide
- FinOps for Resiliency: How to Measure What’s at Risk When Systems Go Down
- Resolving a Post-Azure Migration Cost Increase
- Navigating GenAI Capacity Options
- FinOps X 2025 Cloud Announcements
- AWS Migration Evaluator pricing
- Google Cloud Migration Center cost estimation
- AWS Data Transfer Costs: The Complete 2026 Guide
- FASB Accounting Standards Update 2018-15
