Microservices/serverless, AWS Lambda example AWS Lambda is a core component for building serverless microservices, allowing you to run code without managing servers. The most common example of this architecture involves  combining  Amazon API Gateway  with  AWS Lambda  and  Amazon DynamoDB  to create a fully serverless, event-driven API .   Serverless Microservice Architecture Example (API-driven) This pattern is ideal for creating discrete, independent services that handle specific tasks over HTTP requests, such as processing payments or managing user data.   Key Components Amazon API Gateway : Acts as the "front door" for the microservice, handling API calls (e.g., GET, POST) and routing them to the appropriate backend service. AWS Lambda : The compute service that runs your business logic in response to events (in this case, an API request). You only pay for the exact compute time consumed. Amazon DynamoDB : A serverless NoSQL database used to store and retrieve data for the microservice.   Example Scenario: "Order Processing" Microservice Imagine a large e-commerce application that needs a dedicated service for handling new orders. 1. The Request: A user clicks "Place Order" on the website. A front-end application makes a  POST  request to the  /orders  endpoint exposed by the Amazon API Gateway.   2. Event Trigger & Compute: API Gateway receives the request. It is configured to trigger a specific AWS Lambda function (e.g.,  processOrderFunction ). AWS Lambda automatically runs the associated code without you needing to provision or manage any server infrastructure.   3. Business Logic & Data Storage: The  processOrderFunction  executes the order processing logic (e.g., validating items, calculating the total). The function then writes the new order details into a dedicated  OrdersTable  in Amazon DynamoDB.   4. The Response: DynamoDB confirms the write operation to the Lambda function. The Lambda function returns a success response to API Gateway. API Gateway sends an  HTTP 200 OK  status back to the user's front-end application.   Other Serverless Patterns Beyond API-driven microservices, AWS Lambda is central to other event-driven patterns:   Data Processing Pipeline:  An object uploaded to an Amazon S3 bucket can trigger a Lambda function to resize an image, convert a file, or analyze metadata. Stream Processing:  Data flowing through Amazon Kinesis or Amazon SQS (Simple Queue Service) can trigger Lambda functions for real-time analytics or decoupled message processing.