Getting Started with AWS Lambda for Serverless Computing > 자유게시판

AWS Lambda enables running code without provisioning servers, paying only for compute time. Functions support multiple languages including Python, Node.js, Java, and Go. Start by creating a Lambda function in the AWS Console or using AWS CLI. Understand the handler function that processes events. Configure triggers from services like API Gateway, S3, or DynamoDB Streams. Set appropriate memory allocation from 128MB to 10,240MB. Lambda cold starts can be mitigated with Provisioned Concurrency. Use environment variables for configuration. Implement logging with CloudWatch Logs. Handle errors with DLQ (Dead Letter Queue) and retry policies. Manage dependencies using Lambda Layers. Use IAM roles for permissions instead of hardcoded credentials. Optimize function size by removing unnecessary dependencies. Implement function URLs for direct HTTP access. Use Step Functions for multiple Lambda functions. Monitor performance with X-Ray tracing. Consider using Lambda@Edge for content delivery customization. Set appropriate timeouts between 1 second and 15 minutes. Use reserved concurrency to prevent runaway costs. Lambda is ideal for event-driven architectures and microservices.