Cloud Computing

Definition

Delivery of computing services over the internet including servers, storage, and software

Classification & Usage

• Type: Infrastructure + Service delivery model (combines hardware data centres, virtualisation software, and network services)
• Where it is used: Nearly every digital product today: streaming platforms (Netflix on AWS), enterprise SaaS (Salesforce, Microsoft 365), mobile backend (Firebase), AI training clusters, government IT (UK Gov Cloud, US FedRAMP), startups’ entire stack, disaster-recovery sites, and hybrid setups linking on-premise data centres to public clouds.
• How it is used: Organisations rent compute, storage and networking via web consoles or infrastructure-as-code tools (Terraform, CloudFormation). Services are offered at three layers: IaaS (EC2, Azure VMs), PaaS (App Engine, Heroku) and SaaS (Gmail, Slack). Workloads auto-scale with demand, are billed per-second or per-request, and are secured through IAM policies, VPCs and encryption keys.

Etymology & Origin

The phrase ‘cloud computing’ derives from the cloud symbol used in telecoms and network-architecture diagrams from the 1970s onward to represent ‘somewhere in the network’ — infrastructure the engineer didn’t need to detail. Computing ‘in the cloud’ thus meant ‘computing delivered from an abstracted, shared elsewhere’. The phrase entered mainstream technical use around 2006 when Amazon Web Services launched EC2 and S3.

Historical Development

Time-sharing mainframes in the 1960s (John McCarthy proposed ‘computing as a public utility’ in 1961) foreshadowed the model. Salesforce pioneered SaaS in 1999. The modern definition was formalized by the U.S. National Institute of Standards and Technology (NIST Special Publication 800-145, 2011) with five essential characteristics: on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service.

Implementation History

Amazon launched S3 in March 2006 and EC2 in August 2006, making pay-per-hour virtual machines universally available. Google App Engine (2008), Microsoft Azure (2010), and later Alibaba Cloud and Oracle Cloud followed. Containerization (Docker, 2013) and orchestration (Kubernetes, 2014) enabled the cloud-native era, and serverless compute (AWS Lambda, 2014) abstracted infrastructure further.

Current Relevance

The global cloud market exceeds $600 billion annually, dominated by AWS, Microsoft Azure, and Google Cloud. Regulatory sovereignty concerns have driven ‘sovereign clouds’ in the EU, India, and China. Hybrid and multi-cloud architectures are standard enterprise practice, with tools like Terraform and Kubernetes abstracting across providers. AI workloads — GPU-intensive training — have become the fastest-growing segment, reshaping data-center power and cooling economics.

Visual References

Examples

• Cloud deployment models include: Public cloud (shared resources), Private cloud (dedicated resources), Hybrid cloud (combined environments). Service models include IaaS (Infrastructure), PaaS (Platform), and SaaS (Software) as a Service.
• Airbnb runs entirely on AWS cloud infrastructure, using services like EC2 for computing, S3 for storage, and EMR for big data processing, enabling them to handle 7 million listings across 220+ countries.

Case Study

Netflix migrated entirely from physical data centers to AWS cloud between 2008-2016. This 8-year journey transformed Netflix from a DVD-by-mail service to the world’s largest streaming platform serving 230M+ subscribers across 190 countries. The cloud enabled Netflix to scale during peak viewing hours and deploy thousands of code changes daily.

Additional Images

Videos

Related Terms

AWS, Azure, Docker, Kubernetes, Serverless

Antonyms

On-premises computing, Local hosting