aws-advanced-patterns

Step Functions orchestrate complex workflows by defining state machines that coordinate Lambda functions, DynamoDB operations, and other AWS services. You write a state machine definition in JSON that specifies task sequencing, error handling, retries, and conditional logic, enabling reliable multi-step automation without managing servers.

Single-table design consolidates all application data into one DynamoDB table using composite keys and overloaded attributes, reducing operational complexity and costs. Use it for applications requiring high throughput, cost optimization, and simplified data modeling compared to multi-table architectures.

EventBridge routes events between AWS services and custom applications using rules that match event patterns and direct them to targets like Lambda, Step Functions, or SNS. This decouples services, enables real-time workflows, and simplifies building resilient, loosely coupled systems across your infrastructure.

Yes, Step Functions support saga orchestration by coordinating multi-step transactions across microservices with built-in compensating transactions for rollback. This pattern ensures consistency in distributed serverless workflows without distributed transaction coordinators.

Production serverless requires CloudWatch Logs, X-Ray tracing, and metrics to monitor Lambda execution, Step Functions state transitions, and DynamoDB performance. These constructs provide visibility into failures, latency, and cost across your orchestrated workflows.

Cost optimization combines right-sized Lambda memory, DynamoDB on-demand or provisioned capacity tuning, reserved capacity for predictable workloads, and efficient EventBridge routing. Advanced patterns eliminate waste by aligning resource allocation with actual demand and traffic patterns.