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A data centre is a physical facility that houses servers, storage, networking and supporting systems. Cloud computing is a way to deliver configurable computing resources over a network, with on-demand self-service, shared resource pools, rapid elasticity and measured usage. They are not competing physical technologies: every cloud service ultimately runs on data-centre infrastructure, while an organisation can operate cloud-like services on equipment it controls. The practical choice is therefore between different ways of owning, operating and consuming infrastructure for a particular workload. This guide explains the distinction, the cloud service and deployment models, and a requirements-based way to compare control, scaling, security, portability and total cost.
What is the difference between a data centre and cloud computing?
The simplest distinction is facility versus delivery model. A data centre is the place and physical infrastructure: buildings, power systems, cooling, racks, servers, storage devices and network equipment. Cloud computing is an operating and commercial model that makes computing resources available through a network as a service.
The National Institute of Standards and Technology (NIST) defines cloud computing by five characteristics: on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service. Its definition is intended as a comparison tool, not as a claim that every hosted service is automatically “cloud.” See NIST SP 800-145.
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|---|---|---|
| What it is | A physical site and the infrastructure installed there | A network-delivered method for provisioning and consuming computing resources |
| Where resources exist | In equipment owned or directly controlled by an organisation or facility operator | In a provider’s infrastructure, an organisation’s private infrastructure, or a combination |
| How capacity is obtained | Buy, lease or colocate equipment and add capacity through projects | Request resources through a portal, API or managed service and adjust them as needed |
| Who operates what | The organisation or its facility partner decides which hardware and controls to run | Responsibility is divided between customer and provider according to the service model |
| Defining idea | Physical infrastructure and its operating environment | Abstraction, pooling, automation, elasticity and measured use over a network |
NIST describes cloud infrastructure as having a physical layer—typically servers, storage and network components—and an abstraction layer that enables cloud characteristics. Consequently, “moving to the cloud” means changing how resources are provisioned and managed; it does not remove the underlying machines. The NIST glossary explains this relationship at Cloud infrastructure.
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Does cloud computing eliminate the need for a data centre?
No. Cloud services run in data centres. The difference is that a customer normally does not select, purchase or maintain each physical server. A provider operates the facilities and presents virtual machines, storage, databases, applications or other capabilities through an abstraction layer.
An organisation can also build a cloud-like internal service in its own data centre. If teams can request resources through self-service, consume pooled capacity, scale it rapidly and receive measured usage information, the service can exhibit cloud characteristics even though the hardware is on the organisation’s premises. Conversely, a hosted service that lacks those characteristics may be outsourcing or colocation rather than cloud computing.
This distinction prevents two common errors:
- “On-premises” does not automatically mean non-cloud. Location describes where equipment is; cloud describes how resources are delivered and managed.
- “Cloud” does not mean infrastructure-free. Physical servers, storage, networks, power and cooling still exist; the customer’s visibility and responsibilities change.
What are the defining characteristics of cloud computing?
NIST’s five characteristics provide a practical test for whether an offering has cloud properties. They describe behaviour, not a particular vendor or building.
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On-demand self-service
A customer can provision capabilities such as server time or storage when needed, without requiring a human administrator at the provider to perform each request. Self-service may be delivered through a web console, an API, infrastructure-as-code or an automated service catalogue.
Broad network access
Capabilities are available over a network using standard mechanisms and can be reached by appropriate client platforms. The requirement is not that every service be publicly reachable; a private cloud can restrict access while still providing network-based access to authorised users.
Resource pooling
The provider pools computing resources to serve multiple customers, assigning and reallocating capacity dynamically according to demand. Customers generally have location independence: they may know a geographic region or availability zone, but not the exact physical server.
Rapid elasticity
Resources can be provisioned and released quickly enough to appear, from the customer’s perspective, almost unlimited and available in the needed quantity. Elasticity is more than owning spare servers; it depends on automation, pooled capacity and an operational process that can respond to changing demand.
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Measured service
Use is monitored, controlled and reported according to the type of service, such as storage consumed, requests processed or compute time. Metering supports chargeback, showback, capacity management and provider billing, although the exact metrics and billing rules differ by service.
How do cloud service models differ?
Service models describe what the provider supplies and what the customer manages. They should not be confused with deployment models, which describe where and for whom the cloud environment is operated.
| Service model | Provider generally supplies | Customer generally manages | Typical use |
|---|---|---|---|
| Infrastructure as a Service (IaaS) | Underlying cloud infrastructure, including physical computing, storage and networking, plus the virtualisation or equivalent control layer | Operating systems, storage configuration, deployed applications and many network and security settings | Lift-and-shift workloads, custom applications and environments requiring operating-system control |
| Platform as a Service (PaaS) | Infrastructure, operating system and application platform components such as runtimes, middleware and managed databases, depending on the offering | Application code, data and application-level configuration | Building and deploying software without maintaining the underlying operating system |
| Software as a Service (SaaS) | The complete application and the infrastructure and platform that run it | User accounts, data, permissions and configuration exposed by the application | Using a finished business or productivity application through a browser or client |
NIST’s service-model descriptions are set out in SP 800-145. The boundaries are not identical for every product: a managed database may remove operating-system duties while still exposing database-level controls, so read the provider’s responsibility matrix rather than relying on the label alone.
What are the cloud deployment models?
Deployment models describe the intended users and ownership arrangement. They are a separate dimension from IaaS, PaaS and SaaS; for example, a private cloud can offer IaaS, and a public cloud can offer SaaS.
- Public cloud: infrastructure is made available for use by the general public and operated by a provider.
- Private cloud: infrastructure is provisioned for the exclusive use of one organisation. It may be owned, managed or located by that organisation or a third party.
- Community cloud: infrastructure is shared by a specific community of organisations with common concerns, such as mission, security or compliance requirements.
- Hybrid cloud: two or more distinct cloud infrastructures remain separate but are connected to enable data or application portability, workload movement or coordinated operation.
These categories come from NIST’s definition and project material. A provider’s public cloud and an organisation’s private cloud can both use physical data centres; the deployment label does not by itself establish security, performance or cost.
Which gives an organisation more control?
A directly operated data centre usually gives the organisation more control over physical equipment, hardware selection, network design, maintenance windows and the location of data. That control also creates responsibility for procurement, lifecycle replacement, firmware, facilities, redundancy, physical security and specialist staff.
Cloud control is layered. In IaaS, the customer normally controls the guest operating system, storage configuration and deployed applications while the provider operates the underlying cloud infrastructure. In PaaS and SaaS, the provider manages progressively more of the stack. This can reduce undifferentiated operations, but it also limits low-level customisation and makes the provider’s interfaces and policies part of the design.
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Document the boundary for each workload in a responsibility matrix. List who controls physical access, hypervisors, operating systems, identity, network rules, encryption keys, backups, patching, application code and data retention. A contract that says “managed” without naming these controls is not sufficient for an audit or incident response plan.
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How do provisioning and scaling compare?
Cloud services are designed for on-demand provisioning and rapid elasticity, so a team can often create or release resources through a console, API or automation pipeline. Capacity can scale with demand when the chosen service, quotas, architecture and region support it.
In a conventional data centre, scaling normally requires forecasting, purchasing or leasing equipment, installing it, connecting it to power and networks, and integrating it with monitoring and security. A well-automated private environment can shorten these steps, but it still has finite physical capacity and a capital-replacement cycle.
Elasticity is not unlimited or automatic. Check service quotas, scaling limits, startup time, stateful-system behaviour, licensing constraints, network throughput and the cost of idle capacity. A workload that cannot be partitioned or restarted may gain little from a nominally elastic platform.
Which option fits a particular workload?
Neither a data centre nor cloud computing has a universal performance advantage. Evaluate the workload’s resource profile and operational constraints instead of assuming that one location is faster.
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|---|---|---|
| Is demand steady or highly variable? | Variable demand can benefit from elastic provisioning; steady demand may make dedicated capacity easier to forecast. | Peak and average CPU, memory, storage, requests, users and concurrency over representative periods |
| Does it require specialised hardware? | GPUs, low-latency devices, unusual accelerators or custom networking may be available only in selected environments. | Supported hardware, driver versions, reservation rules and supply lead times |
| Where are users and data located? | Distance, network paths and residency rules affect latency and architecture. | Measured latency, bandwidth, routing, regional availability and legal requirements |
| Is the workload stateful or tightly coupled? | Databases and clustered systems may scale differently from stateless web tiers. | Replication method, failover time, storage IOPS, consistency and recovery objectives |
| What operational constraints apply? | Maintenance windows, disconnected operation, hardware certification or deterministic timing can rule out otherwise suitable services. | Change policy, outage tolerance, support commitments and certification requirements |
Run a representative proof of concept when performance is material. Measure the same application, data shape, network path and security controls in each candidate environment; do not substitute a provider’s generic benchmark for workload-specific evidence.
Is a data centre or cloud more secure?
There is no categorical winner. Security depends on the specific controls, architecture, implementation and operating arrangement. A private facility may offer direct physical and network control but can suffer from unpatched systems or weak monitoring. A cloud provider may offer mature security services and specialist operations while introducing shared-responsibility, identity, configuration and supplier-dependency risks.
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NIST identifies security as a challenge in wider cloud adoption. Compare controls rather than labels, including:
- Identity federation, least privilege, privileged-access management and multi-factor authentication
- Encryption in transit and at rest, key ownership and key-rotation procedures
- Tenant isolation, segmentation, firewall policy and administrative logging
- Vulnerability management, patch responsibilities and secure configuration baselines
- Backup immutability, recovery testing, ransomware response and incident notification
- Physical access controls, personnel screening and independent assurance reports
- Data residency, retention, deletion and lawful-access processes
Map each requirement to an accountable party and obtain evidence in the service documentation and contract. A provider’s certification can support due diligence, but it does not replace the customer’s configuration, identity or application-security responsibilities.
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Start with the workload’s obligations, then test whether the proposed service can meet them. Identify the permitted jurisdictions, retention period, recovery point objective (RPO), recovery time objective (RTO), audit requirements and any sector-specific controls. Confirm that the service’s regions, backups, support process and subcontractors align with those obligations.
For a data centre, assess power and cooling redundancy, generator and fuel arrangements, fire protection, physical access, network-carrier diversity, hardware spares and recovery procedures. For cloud, assess region and availability-zone design, service-level commitments, quota failure modes, control-plane dependencies and the provider’s incident and exit processes. In either case, resilience is an engineered property that must be demonstrated through testing.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do portability and interoperability affect the choice?
Portability is the ability to move applications or data; interoperability is the ability of systems to work together. NIST lists both as cloud-adoption challenges. A workload can be technically portable yet expensive or slow to move because of data volume, proprietary services, licensing, network egress, reconfiguration or retraining.
Before committing, inventory dependencies: proprietary databases, identity services, message formats, APIs, infrastructure-as-code, observability tools, backup formats and encryption keys. Define an exit procedure that includes data export, validation, parallel operation, DNS and certificate changes, user migration, deletion confirmation and the people responsible for each step.
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Using containers or open interfaces may improve portability, but it does not guarantee equivalent performance or features elsewhere. Keep critical data in documented formats, test exports periodically and record the time and bandwidth required to restore an independent copy.
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Which is cheaper: a data centre or cloud?
There is no general price rule. Compare the full cost of the specific workload over its expected life and usage pattern. NIST’s evaluation guidance recommends matching customer requirements with provider capabilities rather than selecting a universal model; see SP 500-322.
| Cost area | Data centre costs to include | Cloud costs to include |
|---|---|---|
| Infrastructure | Servers, storage, networking, racks, power distribution, cooling and facility rent or construction | Compute, storage, managed services, reserved capacity or committed use, and minimum charges |
| People | Facilities, hardware, network, systems, security and operations staff | Cloud engineering, architecture, FinOps, security, support and migration staff |
| Connectivity | Carrier circuits, cross-connects, internet transit and remote-site links | Private links, VPNs, load balancing, data transfer and possible egress charges |
| Resilience | Redundant equipment, backup sites, replication, spares and disaster-recovery testing | Multi-zone or multi-region duplication, snapshots, backup storage, recovery traffic and testing |
| Lifecycle and risk | Refresh projects, unused capacity, warranties, disposal and outage impact | Idle resources, price changes, licence terms, migration and exit costs |
Model at least a steady-load case, a peak-demand case and a growth or contraction case. Separate one-time migration and equipment purchases from recurring operating costs, and include the financial effect of downtime and delayed provisioning. A cloud bill that reflects measured use is not automatically lower; unused instances, oversized databases, backup retention and data transfer can dominate the total.
How should an organisation decide?
Use a workload-by-workload decision rather than choosing a label for the entire organisation. The following process produces an auditable comparison.
- Define requirements. Record performance targets, availability, RPO, RTO, data location, security controls, retention, integrations, support hours and growth range.
- Classify the workload. Note whether it is latency-sensitive, seasonal, stateful, regulated, hardware-dependent, internet-facing or suitable for automation.
- List viable architectures. Include directly operated infrastructure, colocation, private cloud, public-cloud IaaS/PaaS/SaaS and hybrid designs where justified. Do not treat colocation as cloud unless the service actually provides cloud characteristics.
- Map responsibilities. For every control, identify the accountable party and the evidence available for audit, incident response and recovery.
- Test technical fit. Measure representative performance, network behaviour, scaling, backup and restore, monitoring and failure handling.
- Model total cost. Use expected usage, peaks, staffing, connectivity, resilience, licences, migration and exit—not just the headline hourly or monthly rate.
- Assess portability. Document proprietary dependencies, export formats, transfer time, contract notice periods and a tested exit path.
- Make a reversible first move. Pilot a bounded workload, set success criteria and retain rollback or parallel operation until the criteria are met.
The outcome may be mixed: for example, a stable specialised system could remain in a controlled facility while customer-facing services use elastic cloud capacity. A hybrid design adds integration and governance work, so use it when the requirements justify that complexity rather than as a default compromise.
What mistakes should be avoided?
- Equating cloud with someone else’s data centre. Ask whether the service provides the five cloud characteristics and document the physical and abstraction layers.
- Assuming the service label defines responsibility. Read the actual responsibility matrix for the selected IaaS, PaaS or SaaS offering.
- Ignoring network and data movement. Include latency, bandwidth, transfer charges, replication traffic and the ability to operate during a link failure.
- Calling elasticity unlimited. Check quotas, regional capacity, licensing and the scaling behaviour of stateful components.
- Choosing on security marketing alone. Compare concrete controls, evidence, obligations and incident procedures.
- Leaving exit until termination. Test exports, restores and a replacement architecture before the contract or platform becomes critical.
- Comparing only purchase price. Include people, facilities, resilience, migration, idle capacity and the cost of outages.
What does NIST say about using the definition?
NIST’s 2011 publication describes the definition as a way to establish consistent terminology and compare implementations. In the announcement for the final version, NIST computer scientist Peter Mell said: “When agencies or companies use this definition, they have a tool to determine the extent to which the information technology implementations they are considering meet the cloud characteristics and models.” The statement is attributed in NIST’s October 25, 2011 announcement; it is not a recommendation of a particular provider.
NIST’s cloud project overview, updated September 14, 2026, continues to identify security, interoperability and portability as important considerations. Use the definition and evaluation guidance as a vocabulary and checklist, then assess the actual service, contract and workload evidence.
Frequently Asked Questions
Can a company have both an on-premises data centre and cloud services?
Yes. Many organisations place different workloads in different environments or connect a private environment to a public service. The design must specify identity, network routing, data synchronisation, monitoring and which system remains authoritative during an outage.
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No. Colocation usually provides space, power, cooling and connectivity for equipment that the customer owns or leases. It becomes cloud-like only when the delivered service also provides characteristics such as self-service provisioning, pooled resources, rapid elasticity and measured use.
What does “shared responsibility” mean in cloud contracts?
It means the provider and customer each perform different security and operational tasks. The exact split changes by service: a SaaS provider may manage the application platform while the customer still controls identities, permissions, data and configuration.
How can I estimate cloud data-transfer costs before migrating?
Measure current and projected ingress, egress, replication, backup and user traffic by region and destination. Apply the candidate service’s published transfer rules to those volumes, then validate the estimate with a small, instrumented pilot because architecture changes can alter traffic patterns.
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