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Leaving the cloud can make sense when a company has steady, substantial workloads, can operate production infrastructure, and finds that recurring cloud costs outweigh the value of managed services and instant capacity. It is not a general rule that owned servers are cheaper or safer. The decision depends on workload patterns, the full cost of operating both options, staff capability, recovery design, and how quickly new capacity must be available.
Why are some companies leaving the cloud?
“Cloud repatriation” usually means moving workloads from public-cloud services to infrastructure a company owns or rents in a professional data center. The move can be partial: a company might bring predictable compute workloads onto its own servers while retaining cloud services for bursts, specialized managed services, or particular locations.
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For a business with stable demand, cloud bills can become a large recurring expense even when capacity is used consistently. An organization that already has the people and skills to run production systems may find it worthwhile to compare that expense with servers, colocation, operations, and replacement costs. By contrast, a new product with uncertain demand may benefit more from avoiding upfront commitments and using managed services.
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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minute37signals, the company behind Basecamp and HEY, offers a prominent example, not a universal cost formula. In an October 19, 2022 essay, co-owner and CTO David Heinemeier Hansson described the company as medium-sized, with stable growth, and argued that cloud had not reduced its operations headcount. He wrote that HEY was then paying more than $500,000 per year for Amazon database and search services. That is a historical company figure for 2022, not a current price or a typical bill.
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What did 37signals move, and what did it estimate saving?
37signals said it moved Basecamp, HEY, and five other legacy applications from AWS to owned hardware in 2023. Its December 2023 FAQ says the move was completed in June. The company describes a shift away from public-cloud virtual machines and managed services toward owned servers in professional data centers—not the construction of a company-owned data center.
The figures below are company-reported estimates and configuration details. They are not independently audited savings, a neutral comparison for other businesses, or a recommended server build.
| Figure | What it describes |
|---|---|
| More than $500,000 per year | HEY’s database and search services, as described by David Heinemeier Hansson in an October 19, 2022 essay; a historical company figure for 2022. |
| $3.2 million | 37signals’ reported cloud spending during 2022, cited in its February 2023 estimate. |
| Just under $1 million | 37signals’ reported 2022 expense for storing 8 petabytes in S3. The company said the initial 2023 effort focused on compute and related server costs, with leaving S3 planned separately. |
| About $7 million over five years | 37signals’ projected server-expense savings in its February 21, 2023 estimate. |
| About $10 million over five years; 50–66% lower infrastructure costs | 37signals’ later estimates on its cloud-exit overview, accessed in 2026. These are company estimates, not independently verified realized savings. |
The later estimate should not be confused with the earlier projection: both are 37signals figures published at different points in the project. Neither establishes what another company would save, or whether the estimate represents realized net savings after every cost is counted.
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The hardware and operating model
In an April 2023 hardware update, 37signals said it had received 20 Dell R7625 servers for its Chicago and Ashburn locations. The company reported nearly 4,000 vCPUs, 7,680 GB of RAM, and 384 TB of Gen 4 NVMe capacity across the new servers. Those figures describe its own fleet and should not be treated as a sizing guide for a typical business.
In its December 2023 FAQ, the company said its operations team did not change in size, that each of its two data centers could carry the full required load, and that critical infrastructure was replicated. Its cost model assumed a five-year server life. These are details of 37signals’ design and assumptions, not proof that another organization can match the results with the same staffing or equipment.
When does owned infrastructure deserve a serious comparison?
Do not decide from a single cloud invoice or a general claim about “cloud waste.” Compare the shape of the workload and what each option requires the organization to do. The table is a decision framework, not a break-even calculator; there is no universal threshold in the available company case.
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| Decision factor | Cloud may fit better when… | Owned or colocated infrastructure merits analysis when… |
|---|---|---|
| Demand | Usage is highly irregular, scale is uncertain, or recurring peaks are many times the baseline. | Baseline demand is stable and growth is predictable enough to plan capacity. |
| Cost and services | Fast provisioning or managed services provide value that justifies their cost. | Recurring compute, database, storage, or managed-service charges remain substantial after optimization. |
| People | The organization lacks the capability to run production infrastructure and benefits from a managed starting point. | Staff already operate production systems and can take on ownership without relying on an unrealistic staffing assumption. |
| Resilience | A provider’s services simplify a design the team cannot otherwise operate. | The organization can fund and operate replicas, backups, failure testing, and geographically separated capacity. |
| Provisioning and geography | Capacity must be available quickly or in many locations. | Hardware lead times are manageable, while a CDN or selected cloud capacity can serve edge locations or bursts. |
| Migration risk | Provider-specific managed services are hard to replace or exiting them would create unacceptable risk. | The team can replace dependencies, move data, validate behavior, and operate the target platform. |
Demand spikes can change the answer
37signals’ December 2023 FAQ says bringing new capacity online can take weeks rather than seconds. It suggests that recurring demand spikes of 5–10 times baseline or larger can favor cloud, or a hybrid approach that buys capacity for ordinary demand and rents extra capacity for peaks. That is the company’s guidance, not a universal cutoff: the consequences of a missed peak, how often spikes occur, and the cost of keeping spare capacity all matter.
Is cloud computing always cheaper?
No. Nor does the 37signals example prove that owning servers is always cheaper. Cloud charges can be economical when they replace substantial capital commitments, reduce operations work, or make flexible capacity and managed services valuable. Owned infrastructure can merit a closer look when a company pays heavily for steady use and can operate the alternative.
A fair comparison should use the same workload, service levels, and time horizon on both sides. Include more than server purchase price and monthly compute charges:
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- Cloud side: compute, databases, search, storage, backups, network transfer, support, managed services, and any charges tied to how data is accessed or moved.
- Owned or colocated side: servers and replacement cycles, colocation, power and connectivity where applicable, spare parts, monitoring, backups, security work, staff time, and the cost of maintaining capacity for failures and growth.
- Transition side: engineering time, data transfer, parallel operation during cutover, service changes, testing, and the cost of delays or rollback.
- Risk and service level: recovery targets, geographic redundancy, capacity during failures, and the operational consequences of an outage.
Choose an explicit comparison horizon and state assumptions about utilization, growth, hardware life, and staffing. 37signals used a five-year server-life assumption; another organization’s equipment life, refresh schedule, and workload could differ. If a cost estimate depends on excluding migration work, backup capacity, or staff effort, make that visible rather than presenting it as a like-for-like saving.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Does leaving the cloud eliminate operations or security work?
No. Physical ownership changes who provides and operates parts of the infrastructure; it does not remove the need to deploy, monitor, patch, secure, back up, and recover systems. 37signals says its team remained the same size and describes ongoing responsibilities that include hardware procurement, deployments, security, redundancy, and work with professional data-center providers.
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Likewise, “on-premises” does not have to mean operating a building full of servers. 37signals used professional data centers in separate locations and said each site could support its required load. A company considering this route should distinguish ownership of hardware from responsibility for facilities: colocation can provide the site, power, and connectivity, while the customer remains responsible for the systems it owns and runs.
What does cloud repatriation involve?
Use a staged evaluation. The following sequence is practical guidance based on the work and trade-offs described in the 37signals case; it is not a procedure the company published as a general migration checklist.
- Measure the workload. Gather cloud bills and usage data across representative periods. Separate steady demand from peaks, and identify growth, storage, data-transfer, and availability requirements.
- Map service dependencies. List virtual machines, databases, search, object storage, backups, networking, deployment systems, and other managed services. Note which features are provider-specific and what could replace them.
- Build a comparable cost model. Estimate the full costs of cloud, owned or colocated hardware, and a hybrid. State the hardware-life assumption, staff effort, redundancy, spare capacity, migration, and parallel-running costs.
- Design for failure before buying capacity. Decide how systems will continue or recover if a server, site, network path, or deployment fails. Specify backups, replication, geographic separation, recovery targets, and how the design will be tested.
- Test a small, representative service. Move a service that can reveal operational and compatibility issues without putting the whole business at risk. Validate performance, backups, restores, deployments, monitoring, and rollback before expanding scope.
- Set migration and exit criteria. Define what successful operation and acceptable cost look like, who owns each operational duty, and the conditions that would pause or reverse the move. Keep the option to retain cloud capacity where it still fits.
The migration itself can be harder when data is large, applications depend on managed services, or the target must meet strict recovery requirements. The 37signals case describes open-source database and search alternatives, a CDN for international content delivery, and a separate plan for its S3 exit. It illustrates that a cloud exit can involve replacing individual services and handling data separately rather than moving everything in one step.
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Cloud, owned infrastructure, or a hybrid?
The right choice may differ by workload inside the same company. Keep cloud services where rapid provisioning, geographic reach, managed capabilities, or burst capacity justify their cost; examine ownership where demand is steady and the organization can operate it responsibly. A hybrid design is not automatically simpler—it still needs clear boundaries, data flows, recovery plans, and cost tracking—but it avoids treating every application as if it had the same needs.
37signals’ experience demonstrates that a company with stable workloads and an experienced operations team may choose to leave public cloud and build a multi-site operating model. Its savings and staffing outcomes remain specific to that company. For any other organization, the decision should follow a workload-level comparison of total cost, flexibility, migration risk, people, and resilience—not a slogan for or against cloud.
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