The Economics of Cloud Repatriation
Cloud was supposed to be cheaper. For many organizations, it was, until it wasn't. This guide breaks down the real numbers behind moving workloads back to owned hardware and helps you evaluate whether repatriation makes sense for your situation.
The figures below are a snapshot of what was publicly documented when this guide was written, so read them as a starting point rather than as a quote. What Datacenter.Dev works on now is a compiler for new silicon, one layer under the question of whether to own the machines at all.
Where the Money Goes
Public cloud pricing is designed around convenience and variable demand. You pay per hour of compute, per GB of storage, per GB of data transfer, per million API calls, per log line ingested. These individual line items look small. They add up fast.
A typical mid-size SaaS company spending $30,000 to $80,000/month on AWS will find that roughly 40% goes to compute (EC2 or ECS), 20% to storage and databases (RDS, S3, EBS), 15% to data transfer (egress fees), and 25% to managed services (load balancers, DNS, logging, monitoring, secrets management).
The managed services category is where cloud margins are highest. CloudWatch, Secrets Manager, ALBs, and Route 53 are convenient, but you are paying 5x to 20x what the underlying compute and storage would cost on owned hardware. These are also the easiest workloads to repatriate because open-source equivalents (Prometheus, Grafana, Caddy, Vault) are mature and well-documented.
The 60% Rule
Across publicly documented case studies, organizations that repatriate report saving between 50% and 80% on infrastructure costs. Some specific examples:
Basecamp / 37signals
Began leaving AWS in 2022 and finished the storage exit in 2025, deleting the account. David Heinemeier Hansson initially projected around $7M of savings over five years and later revised that upward to more than $10M, saying the result came in better than estimated. By 2024, the first clean year, the remaining cloud bill was about $1.3M, roughly $2M a year lower than before.
Dropbox
Began moving off S3 to its own storage system, Magic Pocket, in 2015. Filings made before the 2018 IPO showed roughly $75M in operating costs saved across two years, and gross margin rising from 33% to 67%. Their core storage workload was predictable and high volume, which is the profile that repatriates well.
Source: GeekWire, on Dropbox pre-IPO filings(opens in a new tab)
Small and mid-size businesses
You do not need Dropbox-scale to benefit. A company spending $5,000/month on cloud can often move to two refurbished servers for $3,000 to $5,000 total, plus $200 to $400/month in colocation or power costs. Payback in 2 to 4 months, then 60 to 80% ongoing savings.
The VMware Catalyst
Broadcom's acquisition of VMware in late 2023 triggered a licensing earthquake. Per-core pricing replaced per-socket. Perpetual licenses were killed. Subscription bundles forced customers to buy products they did not want. In ETR's December 2025 survey, 71% of respondents said prices had risen substantially more than the broader software market, and European cloud providers in CISPE reported increases between 800% and 1,500%.
Source: ETR, VMware customers face a cost reckoning, December 2025 survey(opens in a new tab)
Source: Network World, on CISPE members' reported VMware price increases(opens in a new tab)
For organizations already running on-premises VMware infrastructure, this created an urgent decision: absorb the cost increase, migrate to a different hypervisor, or move to public cloud. Many chose to re-evaluate from scratch, and discovered that the math favors owning when you replace VMware with open-source alternatives like Proxmox VE.
Proxmox VE is free to download and run. Enterprise support subscriptions start at a fraction of VMware licensing costs. The feature set covers KVM virtualization, LXC containers, ZFS storage, Ceph clustering, and built-in backup. For most workloads, it's a direct replacement.
Hardware is Cheap
The price of server-grade hardware has dropped steadily while performance has increased. A refurbished Dell PowerEdge R730 with 256GB RAM and dual Xeon processors can be had for $500 to $800. That is equivalent to an r5.8xlarge EC2 instance, which costs roughly $2,000/month on-demand or $800/month reserved.
The hardware pays for itself in under one month at on-demand rates, or under two months with reserved pricing. After that, your only costs are power ($30 to $80/month for a single server), internet, and optionally colocation ($50 to $200/month per U).
For newer hardware, a current-generation AMD EPYC server with 128 cores and 512GB RAM runs about $5,000 to $8,000. The equivalent cloud compute would cost $4,000 to $6,000 per month. Payback: 1 to 2 months.
The pattern holds across the board. For predictable, steady-state workloads, owned hardware is 5x to 10x cheaper than cloud over a 3-year period. The cloud advantage is elasticity for unpredictable spikes, which is why the optimal approach for most organizations is a hybrid model: own your baseline, burst to cloud for peaks.
The same arithmetic gets more interesting as you move off mainstream x86. Parts built for inference change the price per unit of work, and getting a model running on one is largely a solved problem now. What's left is showing that it computes the same numbers on the new part as it did on the old one, and what establishes that today is testing. Past a point more of it stops raising confidence that the two agree. That limit is the Verification Wall, and it's where Datacenter.Dev's own work went.
When NOT to Repatriate
Repatriation is not the right answer for every workload. It generally does not make sense when:
- •Your workload is highly variable. If your compute needs spike 10x during certain hours and drop to near zero otherwise, on-demand cloud pricing may still be cheaper than buying hardware for peak capacity.
- •You are a tiny startup still finding product-market fit. If your infrastructure needs change every month, the flexibility of cloud outweighs the cost savings of owned hardware. Repatriate when your workload stabilizes.
- •You rely heavily on managed services you cannot replace. Some cloud-native services (DynamoDB, BigQuery, Aurora Serverless) have no straightforward self-hosted equivalent. If your architecture depends on these, migration cost may outweigh savings.
For everything else, especially steady-state compute, storage, databases, CI/CD, AI inference, and internal tools, the math strongly favors owning.
Ready to Run the Numbers?
Pull your last 3 months of cloud bills. Identify your top 5 line items by cost. For each one, ask: is this workload predictable? If yes, price out the equivalent hardware. The savings will likely surprise you.