Data science & AI · Reference
What is cloud computing?
Cloud computing is the on-demand delivery of computing resources — such as servers, storage, databases, and software — over the internet, allowing users to access scalable capacity without owning the underlying hardware.
Essential characteristics
The widely used NIST definition lists five essential characteristics of cloud computing: on-demand self-service (users provision resources automatically), broad network access (available over the network from many devices), resource pooling (shared infrastructure serving many users), rapid elasticity (capacity scales up and down quickly), and measured service (usage is metered and billed). Together these distinguish cloud computing from simply renting a remote server, emphasising automation, scalability, and pay-for-what-you-use economics.
Service models: IaaS, PaaS, SaaS
Cloud services are commonly grouped into three models. Infrastructure as a Service (IaaS) provides fundamental resources — virtual machines, storage, networking — that the user configures.
Platform as a Service (PaaS) provides a managed environment for building and running applications, hiding the underlying infrastructure. Software as a Service (SaaS) delivers complete applications over the internet, with the provider managing everything beneath. The models trade control for convenience: IaaS offers the most control, SaaS the least operational burden.
Deployment models
Clouds are also categorised by who can use them. A public cloud is shared infrastructure offered to the general public by a provider. A private cloud is dedicated to a single organisation. A hybrid cloud combines the two, allowing data and workloads to move between them. The choice involves trade-offs between cost, control, security, and regulatory or data-residency requirements — considerations that are particularly relevant when handling sensitive research data.
Cloud computing in research
Cloud computing is now a major part of research infrastructure. It lets researchers access large-scale storage and compute on demand — useful for analysing big datasets, running simulations, or sharing data — without maintaining their own data centre. Considerations include cost management, data-transfer constraints, reproducibility of computational environments, and compliance for sensitive data. Aligning cloud-based workflows with research data management and FAIR principles helps keep results reproducible and reusable.
Key facts
At a glance
- Definition: on-demand computing resources over the internet
- Reference definition: NIST (five essential characteristics)
- IaaS: infrastructure (virtual machines, storage, networking)
- PaaS: managed platform for building/running applications
- SaaS: complete applications delivered over the internet
- Deployment models: public, private, hybrid
Common questions
FAQ
What are the three cloud service models?+
Infrastructure as a Service (IaaS) provides raw resources like virtual machines and storage; Platform as a Service (PaaS) provides a managed environment for building applications; and Software as a Service (SaaS) delivers complete applications over the internet.
What is the difference between public, private, and hybrid cloud?+
A public cloud is shared infrastructure offered to many customers by a provider; a private cloud is dedicated to one organisation; and a hybrid cloud combines both so data and workloads can move between them, balancing cost, control, and compliance.
Why is cloud computing useful for research?+
It gives researchers on-demand access to large-scale storage and compute without owning hardware, supporting big-data analysis, simulations, and data sharing. Care is still needed over cost, data-transfer limits, reproducibility, and compliance for sensitive data.
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