π Step Functions Deep Dive
Master Step Functions distributed map, error handling, and workflow patterns.
Module: AWS Data Engineering β’ Topic 46 of 65 β’ Premium Content
Step Functions Patterns
Architecture Diagram
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β STEP FUNCTIONS PATTERNS β
β β
β Distributed Map: β
β β’ Process millions of items in parallel β
β β’ Up to 10,000 concurrent Lambda invocations β
β β’ Results aggregated automatically β
β β’ Great for large-scale ETL β
β β
β Error Handling: β
β β’ Retry with exponential backoff β
β β’ Catch errors and route to fallback β
β β’ Choice states for conditional branching β
β β’ Wait states for delays β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Interview Q&A
Q1: What is Distributed Map?
Answer: A state type that processes large datasets by parallelizing Lambda invocations up to 10,000 concurrent executions.
Q2: How does error handling work?
Answer: Use Retry for automatic retries with backoff. Use Catch to route errors to fallback states. Choice states enable conditional logic.
Q3: What is the difference between Standard and Express workflows?
Answer: Standard: up to 1 year, audit trail, 1/million executions.
Summary
- Distributed Map: Parallel processing up to 10,000 concurrent
- Error Handling: Retry, Catch, Choice for robust workflows
- Standard: Long-running, audit trail
- Express: High-volume, cost-effective
- Integration: Native AWS service integration