Serverless architecture is a cloud computing model where the cloud provider manages the infrastructure required to run code, allowing developers to focus solely on writing and deploying application logic. Instead of provisioning servers or virtual machines, developers package their code into functions or services that the cloud platform executes on demand. For example, AWS Lambda lets developers upload code that automatically scales in response to events like HTTP requests or database changes. The cloud provider handles server allocation, scaling, maintenance, and security patches, abstracting the underlying infrastructure. This integration eliminates the need to manage servers, reducing operational overhead and enabling faster iteration.
Serverless tightly integrates with other cloud services to create event-driven workflows. For instance, a file uploaded to cloud storage (like Amazon S3) can trigger a serverless function to process the file, which might then write results to a cloud database (like DynamoDB) or send a message via a queue (like SQS). APIs built with serverless can use services like API Gateway to route requests to functions, enabling scalable backend systems without managing servers. This event-driven pattern allows developers to build loosely coupled systems where each component reacts to changes in real time. By leveraging existing cloud services for storage, messaging, and authentication, serverless architectures minimize custom code and maximize reuse of managed solutions.
Cost and scalability are key integration points. Serverless platforms charge based on execution time and resource consumption, which contrasts with traditional cloud models where costs are tied to reserved server capacity. For example, a function running for 100ms per invocation costs significantly less than a continuously running virtual machine. This model suits applications with variable or unpredictable traffic, such as APIs or data processing pipelines. However, cold starts (delays when a function initializes) and limits on execution time require careful design. Monitoring tools like AWS CloudWatch or Azure Monitor provide insights into performance and costs. By combining serverless with cloud-native services, developers can build efficient, cost-effective systems that scale seamlessly with demand.