Cloud Computing Vocabulary in English

These are the three main cloud service models. SaaS (Software as a Service) delivers ready-to-use applications over the internet — examples include Gmail, Salesforce, and Microsoft 365. Users simply log in and use the software; the provider handles everything else. IaaS (Infrastructure as a Service) provides virtualised computing resources — servers, storage, and networking — that customers configure and manage themselves. AWS EC2 and Google Compute Engine are IaaS examples. PaaS (Platform as a Service) sits in between: it provides a platform with tools, databases, and a runtime environment for developers to build and deploy applications, without managing the underlying infrastructure. Heroku and Google App Engine are PaaS examples.

Virtualisation is the technology that makes cloud computing possible. It creates virtual versions of physical computing resources — servers, storage devices, and networks — so that one physical machine can run multiple virtual machines simultaneously. Each virtual machine behaves exactly like a dedicated physical server, with its own operating system and resources. This allows cloud providers to use their physical hardware much more efficiently, sharing it among many customers while keeping each customer’s environment separate and secure. Without virtualisation, cloud providers would need vastly more physical hardware to serve the same number of customers.

Scalability is the ability of a cloud system to automatically increase or decrease its computing resources in response to changing demand. For businesses, this is one of the most important advantages of cloud computing. A traditional business that hosts its own servers must buy enough hardware to handle its peak load — which means that hardware sits idle most of the time. With cloud scalability, a business pays only for what it uses and can scale up within minutes when demand spikes (for example, during a product launch or a seasonal sale) and scale back down when demand falls. This makes cloud computing significantly more cost-effective and flexible than traditional on-premises infrastructure.

A public cloud is owned and operated by a third-party provider and shared by multiple organisations over the internet. It offers cost-effective, flexible services but the customer shares the underlying physical infrastructure with others. A private cloud is dedicated to a single organisation, either on its own premises or hosted by a provider. It offers greater control and security but at higher cost. A hybrid cloud combines both, allowing data and applications to move between private and public environments. Businesses often use a hybrid approach: keeping sensitive data on private infrastructure while using the public cloud for less critical workloads or to handle demand spikes.

Containers are lightweight software packages that bundle an application together with all its dependencies — libraries, configuration files, and runtime environment — into a single unit. This ensures the application runs consistently regardless of where it is deployed, whether on a developer’s laptop, a test server, or a production cloud environment. Docker is the most widely used container technology, and Kubernetes is the leading platform for managing large numbers of containers at scale. Containers use fewer resources than traditional virtual machines because they share the host operating system rather than each running their own. They are fundamental to modern DevOps practices and microservices architectures.

Latency is the time delay between a request being made and the response arriving. In cloud computing, it is typically measured in milliseconds. High latency means slow responses — web pages that take too long to load, video calls that lag, or transactions that feel sluggish. Cloud providers reduce latency by locating data centres close to their customers and by using content delivery networks (CDNs) that cache content near users. For most business applications, latency of under 100ms is acceptable. For real-time applications such as financial trading, online gaming, or remote surgery, even a few milliseconds of latency can be critically important.

Serverless computing is a cloud execution model in which the cloud provider automatically manages the allocation and management of servers. Despite the name, servers still exist — but the developer does not need to think about them. Developers write functions or code that are triggered by events (such as an API call or a database change), and the provider runs that code on demand, scaling automatically. The customer pays only for the milliseconds the code runs, not for idle server time. AWS Lambda, Google Cloud Functions, and Azure Functions are popular serverless platforms. Serverless is well-suited to event-driven architectures, batch processing, and applications with unpredictable or sporadic traffic.

Disaster recovery refers to the strategies, processes, and cloud services used to restore data and IT systems after a disruptive event — such as a hardware failure, cyber-attack, natural disaster, or human error. Cloud computing has transformed disaster recovery: instead of maintaining a costly secondary data centre, businesses can replicate their systems to a cloud environment that can be activated within minutes if the primary system fails. Key metrics in disaster recovery planning include the Recovery Time Objective (RTO — how quickly systems must be restored) and the Recovery Point Objective (RPO — how much data loss is acceptable). Cloud-based disaster recovery is typically faster, cheaper, and more reliable than traditional approaches.

An API (Application Programming Interface) is a set of rules and protocols that allows different software applications to communicate with each other. In cloud computing, APIs are what connect different services, platforms, and applications. When you log in to a website using your Google account, an API connects the website to Google’s authentication service. When an e-commerce site processes a payment, an API connects it to the payment provider. Cloud platforms expose their services through APIs, allowing developers to build applications that use storage, databases, AI services, and other cloud capabilities without needing to know how those services are implemented internally.

Group the words into categories that reflect how cloud systems work: service models (SaaS, IaaS, PaaS), deployment types (public, private, hybrid cloud), infrastructure concepts (virtualisation, data centre, load balancing), application architecture (containers, microservices, serverless, API), and performance and reliability (scalability, uptime, latency, bandwidth, disaster recovery). Use Flash Cards to drill definitions, then read technology news from sources such as TechCrunch, the Verge, or vendor blogs from AWS, Azure, and Google Cloud. Working through free introductory cloud courses, many of which are available in English with subtitles, will help you encounter the vocabulary in rich technical context.