aws-cloud-patterns

Proven AWS patterns for scalable serverless applications include request-driven Lambda API backends, DynamoDB single-table designs, and S3 event processing pipelines. These patterns provide ready-to-use architectures to accelerate data-intensive workloads.

Efficient DynamoDB access patterns utilize single-table design to optimize reads and writes in serverless backends. This approach structures data to match query patterns, reducing latency and avoiding anti-patterns like excessive scans.

Yes, CDK and Terraform patterns are provided to provision AWS serverless infrastructure. These infrastructure patterns define Lambda functions, API Gateway endpoints, and DynamoDB tables as code for consistent deployments.

Common Lambda and API Gateway anti-patterns include tightly coupling business logic, inefficient DynamoDB queries, and synchronous processing where asynchronous S3 event pipelines would scale better. Best practices are documented to avoid these pitfalls.

Build S3 event processing pipelines by triggering Lambda functions directly from S3 events. This serverless pattern processes data upon upload, creating scalable data pipelines without provisioning servers.