aws-advanced-patterns

Implement AWS serverless orchestration patterns with Step Functions and EventBridge.

17|1|Updated Jun 8, 2025

Search Tags:#serverless #aws #resilience #cloud-native #eventbridge #dynamodb #cost-optimization #step-functions #cloud-architecture

Ready to run

npx skills add https://github.com/williamzujkowski/standards --skill aws-advanced-patterns

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: aws-advanced-patterns
Source: https://github.com/williamzujkowski/standards/tree/main/skills/cloud-native/aws-advanced
Command: npx skills add https://github.com/williamzujkowski/standards --skill aws-advanced-patterns

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill provides advanced AWS architecture patterns and services, enabling you to build highly scalable, resilient, and cost-optimized cloud solutions. It simplifies the adoption of complex AWS services, reducing operational overhead and accelerating the development of robust cloud-native applications.

Core Features & Use Cases

Serverless Orchestration: Guides on using AWS Step Functions for complex workflow automation.
DynamoDB Single-Table Design: Teaches advanced data modeling for NoSQL databases to optimize performance and cost.
Event-Driven Architectures: Provides patterns for using Amazon EventBridge to build loosely coupled systems.
Use Case: Design a serverless workflow for processing orders using AWS Step Functions, automatically generating a state machine definition that orchestrates Lambda functions and DynamoDB updates.

Quick Start

Generate an AWS Step Functions state machine definition for a simple order processing workflow.

Frequently Asked Questions about aws-advanced-patterns

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I design a serverless workflow using AWS Step Functions?▼

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.

What is DynamoDB single-table design and when should I use it?▼

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.

How do I build event-driven architectures with Amazon EventBridge?▼

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.

Can I implement saga patterns for distributed transactions in serverless?▼

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.

What observability constructs do I need for production AWS serverless applications?▼

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.

How do I optimize costs in serverless architectures with AWS?▼

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.