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Neither cloud nor colocation is always cheaper. In Uptime Institute’s 2025 survey of 154 respondents who directly compared the two, 47% said colocation was cheaper for provisioning workloads, 29% said public cloud was cheaper, and 22% found costs roughly equivalent. Your result depends on utilization, time horizon, location, resilience requirements, labor, and how much data moves across networks.
What you are actually paying for
Public cloud
Cloud pricing is a stack of metered services rather than a single server rental. AWS describes compute, storage and outbound data transfer as its three fundamental cost drivers. A realistic monthly model should also include:
- Virtual machines, containers, GPUs or other compute, billed hourly or per second depending on the service.
- Reserved-instance, savings-plan or committed-use discounts, with their term and utilization obligations.
- Block, object and database storage, plus IOPS, snapshots, backups, replication and retrieval charges where applicable.
- Managed control-plane services, databases, queues, serverless requests, load balancing and public IP addresses.
- Observability: logs, metrics, traces, monitoring retention and security scanning.
- Inter-zone and inter-region transfer, private connectivity, processing fees and internet egress.
- Technical-support plans, software licenses and marketplace charges.
- Migration, data-transfer and eventual exit work.
Cloud prices vary by provider, region, service tier, contract and date. A calculator estimate is not a complete total-cost-of-ownership figure until these ancillary services and one-time costs are added.
Colocation
Colocation means you buy or finance the servers and networking equipment and place them in a third-party data center. The recurring and one-time cost model normally includes:
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- Server, storage, switches, firewalls, racks and spare equipment; depreciation or financing is the way to spread those capital costs across the analysis period.
- Rack, cabinet or cage fees; metered or committed power; and any cooling or facility pass-through charges.
- Internet transit, bandwidth commitments, cross-connects and other network services.
- Remote-hands work, installation, cabling and after-hours service fees.
- Hardware warranties, maintenance contracts, replacement parts and a reserve for failures.
- Capacity held for peaks, maintenance and hardware redundancy rather than average load alone.
- Software licenses, monitoring, security, insurance, compliance work, staffing and travel.
Colocation does not eliminate operating expense: it moves more of the bill into equipment ownership, facilities and the people responsible for running that equipment.
Why the market has no single price winner
Uptime Institute’s 2025 Data Center Spending Survey found a split result rather than a consensus. Among 154 respondents making a direct comparison, 47% reported that colocation was cheaper for provisioning workloads, 29% reported that public cloud was cheaper and 22% said the costs were about the same. Those responses are a market indicator, not a quote for a particular application: electricity rates, hardware choices, staffing and workload shape differ substantially.
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Power is also a moving colocation input. In Uptime’s 2024 survey results reported in 2025, 70% of enterprise owner/operators identified power as a leading unit-cost increase, compared with 34% identifying bandwidth. A quote that looks attractive today should therefore be tested against likely power and connectivity changes.
Data movement can overturn the calculation
Traffic is often the largest omitted line item in an otherwise careful comparison. Cloud providers may charge for internet egress, inter-zone and inter-region transfer, and network processing. Google’s current pricing page, for example, lists Premium Tier internet egress to destinations in North America and Europe at $0.12 per GiB for the first 1,024 GiB each month; the applicable region, tier and volume must be checked when you model your workload.
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Hybrid designs can have a different economics profile. AWS notes that connectivity costs can include provisioned resources, usage-based transfer and processing, and the connection itself. If your network and the cloud point of presence are in the same colocation facility, the connection may be as little as the cost of a cross-connect. A cross-connect quote, however, does not make the associated cloud transfer, transit, equipment and support costs disappear.
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Build a defensible three- to five-year comparison
A short monthly snapshot can favor cloud simply because it hides hardware capital, or favor colocation because it ignores staff and refresh costs. Use the same three- to five-year horizon for both options and document every assumption.
- Define demand by month. Record CPU or GPU hours, memory, storage consumed, IOPS, inbound and outbound traffic, database size, backup retention and the availability target. Separate baseline demand from peaks.
- Set utilization and growth assumptions. State the average and peak utilization you expect, growth rate, seasonality and spare capacity. A lightly used owned server has a very different cost per unit of work from a highly utilized one.
- Price the cloud case. Apply on-demand rates and any reserved, savings-plan or committed-use discounts to compute. Add storage, databases, snapshots, backups, load balancing, observability, support, licenses, inter-zone and inter-region transfer, internet egress and private connectivity. Include migration-in and a possible exit transfer.
- Annualize the colocation case. Spread server and networking capex or financing over the chosen horizon, then add rack or cage fees, power, cooling pass-throughs, bandwidth, cross-connects, maintenance, spares, remote hands, software, insurance, monitoring, staff time and travel.
- Price resilience rather than assuming it. Include duplicate equipment, spare capacity, multiple power feeds, backup systems, a second site or cloud disaster-recovery environment, replication traffic and recovery testing. Compare the same recovery-time and recovery-point objectives on both sides.
- Add transition and exit costs. Migration engineering, application changes, data seeding, downtime risk, contract termination, hardware disposal and data egress can materially affect the first and last years.
Report a range, not a single break-even month. Recalculate for lower and higher utilization, different power prices, bandwidth growth, hardware-refresh timing, discount expiry and faster-than-expected demand growth. The break-even point is the result of those stated assumptions, not a universal industry constant.
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How the two choices compare in practice
| Decision axis | Public cloud tends to be stronger when | Colocation tends to be stronger when |
|---|---|---|
| Utilization | Demand is uncertain, bursty or seasonal and you can scale down. | Demand is high, stable and equipment can run productively for several years. |
| Time horizon | You need to avoid upfront equipment purchases or may change architecture soon. | You can amortize hardware and facility commitments over a defined multi-year period. |
| Expansion speed | New capacity or regions must be available quickly. | Growth can follow procurement, installation and facility lead times. |
| Geographic reach | You need many regions or want to place services close to worldwide users. | A small number of sites satisfy locality, latency and regulatory requirements. |
| Data movement | Most processing is near the data and outbound traffic is modest or covered by applicable allowances. | Large, predictable flows can remain inside the facility or use economical cross-connects and transit. |
| Operations | You value managed services and want less hardware maintenance. | You have the skills and staffing to operate owned equipment efficiently. |
| Hardware refresh | You prefer the provider to carry refresh and underlying infrastructure responsibility. | You can select specialized hardware and keep it productive through its useful life. |
| Resilience and recovery | Managed regional services or rapid replication simplify the design you need. | You can fund and operate redundant equipment and sites at a known utilization level. |
| Compliance and locality | The provider’s regions, controls and contracts meet the requirement. | Physical custody, a specific facility or custom controls are important. |
| Contract flexibility | You accept variable usage pricing or can use discounts without overcommitting. | You can commit to rack, power and bandwidth terms without stranding capacity. |
| Exit cost | Architecture is portable and data-transfer costs are manageable. | Owned equipment can be redeployed or sold, and the facility contract has a practical exit. |
Questions to ask before accepting a quote
- Which region, currency, tax treatment and price date does each number use?
- Are power and bandwidth metered, committed, capped or subject to pass-through increases?
- Does the cloud estimate include every attached service, support tier, license and log-retention period?
- Does the colocation estimate include installation, remote hands, cross-connects, spares, maintenance and staff travel?
- What utilization is assumed, and how much capacity is reserved for failure, maintenance and growth?
- What are the charges for moving data between zones, regions, the internet, another cloud and the facility?
- Are disaster recovery, backup restoration and recovery testing priced on both sides?
- What happens if demand falls, hardware fails, power prices rise or you leave the contract?
A practical decision rule
Start with measured workload and traffic data, then solicit local colocation quotes and build a provider-specific cloud bill for the same service levels. Cloud is usually the better fit for uncertain demand, rapid expansion, broad geographic deployment or teams that value managed operations. Colocation becomes more compelling when utilization is consistently high and stable, hardware can be amortized for several years, data movement is predictable and you can efficiently carry facilities and operational responsibilities. Treat both statements as hypotheses to test with your own assumptions and sensitivity cases.
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