Serverless Computing — Technology Wiki

Overview

Direct Answer

Serverless computing is a cloud execution model in which developers deploy code without provisioning or managing underlying infrastructure, with the provider automatically scaling resources and charging exclusively for actual execution time measured in milliseconds.

How It Works

Developers package functions or application code, which the cloud provider executes on-demand when triggered by events such as API requests, database changes, or scheduled timers. The platform abstracts infrastructure management, automatically scaling compute capacity across multiple isolated execution environments and terminating instances immediately after code execution completes.

Why It Matters

Organisations reduce operational overhead by eliminating server management responsibilities whilst optimising costs through per-millisecond billing rather than reserved capacity. This model accelerates time-to-market for event-driven workloads and enables teams to focus engineering effort on business logic rather than infrastructure operations.

Common Applications

Real-world use cases include RESTful API backends triggered by HTTP requests, image processing pipelines activated by file uploads to cloud storage, real-time data processing from streaming sources, and scheduled batch jobs. Financial services use this model for transaction processing, whilst media and entertainment organisations employ it for content transformation workflows.

Key Considerations

Cold start latency—the delay when initialising a new execution environment—can impact latency-sensitive applications. Organisations must also evaluate vendor lock-in risks, monitor distributed function behaviour across multiple invocations, and manage stateless architecture constraints.

Related in Service Models

Cloud Computing

The delivery of computing services — servers, storage, databases, networking, software — over the internet on demand.

Infrastructure as a Service

Cloud computing model providing virtualised computing resources like servers, storage, and networking over the internet.

Platform as a Service

Cloud computing model that provides a platform for developers to build, deploy, and manage applications without managing infrastructure.

Software as a Service

Cloud computing model that delivers software applications over the internet on a subscription basis.

Function as a Service

A serverless cloud computing model where individual functions are executed in response to events.

Cloud-Native

An approach to building applications that fully exploit cloud computing advantages like elasticity, resilience, and automation.

Private Cloud

Cloud computing resources used exclusively by a single organisation, either on-premises or hosted by a third party.

Public Cloud

Cloud computing resources shared among multiple organisations and available to the general public over the internet.

Managed Service

A cloud service where the provider handles infrastructure management, maintenance, updates, and monitoring.

Cloud Cost Optimisation

Strategies and practices for minimising cloud computing expenses while maintaining performance and functionality.

Spot Instance

A cloud computing option that uses spare capacity at significantly reduced prices with the possibility of interruption.

Cloud Orchestration

The automated arrangement, coordination, and management of complex cloud computing systems and services.

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Internal Developer Portal

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A centralised web interface that provides developers with self-service access to infrastructure, services, documentation, and templates within their organisation.

Load Balancer

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A device or software that distributes network traffic across multiple servers to ensure no single server is overwhelmed.

OAuth

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Green Cloud Computing

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Cloud computing practices that minimise environmental impact through renewable energy usage, efficient cooling, workload consolidation, and carbon-aware scheduling of compute tasks.

Hypervisor

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Software that creates and manages virtual machines, allowing multiple operating systems to share a single hardware host.

GPU Cloud Computing

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Cloud infrastructure providing on-demand access to graphics processing units optimised for AI training and inference, enabling organisations to scale compute without capital investment.