What is cloud computing?
Understand how on-demand infrastructure and managed services change the way teams provision, scale, pay for, and operate software systems.
What is cloud computing?
Cloud computing is the on-demand delivery of IT resources such as compute, storage, databases, networking, and application services over the internet. A cloud provider owns and operates the underlying facilities and hardware while customers provision the resources and managed capabilities their workloads need.
How this topic fits
Foundations
Start with cloud responsibility, the serverless operating model, and the boundaries between provider-managed infrastructure and application ownership.
How cloud computing works
Cloud providers operate physical data centers, networks, servers, and storage fleets, then expose that capacity through service APIs. A customer can request resources in minutes, configure them with software, and release them when they are no longer required.
The abstraction level varies. Infrastructure services expose virtual machines, networks, and disks. Managed platforms operate more of the runtime and data layer. Serverless services go further by allocating capacity around requests, events, or units of work.
Teams provision resources through APIs and consoles without purchasing or installing physical hardware first.
Resources can expand or contract as demand changes, subject to service design, quotas, and configuration.
Cloud services meter consumption through pricing dimensions such as time, requests, storage, or data transfer.
Infrastructure, platforms, and managed services
Infrastructure as a service gives the customer direct control over virtual compute, storage, and networking while the provider operates the physical layer. Platform and managed services take responsibility for more of the operating system, runtime, scaling, availability, or database work.
The right model depends on how much control the workload requires and how much operational responsibility the team wants to retain. A single system can combine virtual machines, containers, managed databases, and serverless services when the boundaries are deliberate.
Benefits and risks of cloud computing
Cloud computing can shorten provisioning time, provide access to managed capabilities, and let teams match capacity more closely to demand. Global infrastructure and automation can also make recovery and regional deployment options available without building private facilities.
Cloud does not automatically produce a secure, reliable, or inexpensive system. Poor identity policies, unmanaged data movement, idle resources, missing recovery plans, and weak service ownership can create risk quickly. Governance and architecture have to evolve with the speed of provisioning.
How cloud computing leads to serverless
Cloud computing separates application teams from owning physical infrastructure. Serverless extends that separation by reducing direct responsibility for hosts, runtime fleets, and capacity allocation within specific managed services.
That shift changes the unit of design from servers to requests, events, functions, workflows, data, and permissions. The workload still runs on cloud infrastructure, but the application team consumes a higher-level operating model.
Go deeper with AWS
Read the primary AWS documentation behind the service definitions and architecture guidance in this guide.
Next steps
Continue with the concepts that most directly shape this decision.
What is serverless?
Learn what serverless computing means, how it works on AWS, what the cloud provider manages, and which trade-offs still belong to your team.
Choosing serverless compute
Compare AWS Lambda with serverless containers and choose compute from workload duration, runtime control, scaling, isolation, and operating requirements.
What is serverless architecture?
Learn how managed compute, APIs, events, queues, workflows, data, identity, and observability fit together in a serverless architecture on AWS.
Questions about this topic
Browse all serverless concepts
Explore compute, APIs, events, workflows, data, security, reliability, operations, delivery, and AI from one connected AWS serverless learning path.
What is serverless?
Learn what serverless computing means, how it works on AWS, what the cloud provider manages, and which trade-offs still belong to your team.
What is AWS Lambda?
Understand how AWS Lambda runs code, how functions are invoked, where permissions and state live, and when Lambda is a good compute choice.
What is serverless architecture?
Learn how managed compute, APIs, events, queues, workflows, data, identity, and observability fit together in a serverless architecture on AWS.
AWS serverless security
A practical guide to identity, least privilege, event validation, secrets, data protection, dependencies, and incident visibility in AWS serverless systems.
What is agentic AI?
Learn what makes an AI system agentic, how models, tools, memory, orchestration, identity, and evaluation fit together, and where serverless patterns help on AWS.
What is cloud computing?
Understand how on-demand infrastructure and managed services change the way teams provision, scale, pay for, and operate software systems.
What is event-driven architecture?
Learn how producers, routers, and consumers communicate through events, and how to design schemas, delivery, retries, and ownership deliberately.
What is a serverless API?
Understand the request path, authentication, routing, compute, data, throttling, observability, and failure controls behind a serverless API on AWS.
What are serverless workflows?
Learn when explicit workflow state improves retries, branching, parallel work, human approval, visibility, and recovery in distributed applications.
What is Amazon API Gateway?
Learn how API Gateway creates, publishes, secures, monitors, and operates HTTP, REST, and WebSocket APIs for AWS and external backends.
What is Amazon EventBridge?
Understand EventBridge event buses, rules, pipes, schemas, targets, schedules, permissions, delivery, and recovery in event-driven AWS systems.
Make the next serverless decision explicit.
Explore focused products for repeatable work, or bring the architecture decision that needs context and experienced review.