aws-serverless-eda

name	aws-serverless-eda
description	AWS serverless and event-driven architecture expert based on Well-Architected Framework. Use when building serverless APIs, Lambda functions, REST APIs, microservices, or async workflows. Covers Lambd
category	Document Processing
source	antigravity
tags	["python","typescript","node","api","mcp","ai","workflow","design","document","presentation"]
url	https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/aws-serverless-eda

AWS Serverless & Event-Driven Architecture

This skill provides comprehensive guidance for building serverless applications and event-driven architectures on AWS based on Well-Architected Framework principles.

AWS Documentation Requirement

Always verify AWS facts using MCP tools (mcp__aws-mcp__* or mcp__*awsdocs*__*) before answering. The aws-mcp-setup dependency is auto-loaded — if MCP tools are unavailable, guide the user through that skill's setup flow.

Serverless MCP Servers

This skill leverages the CDK MCP server (provided via aws-cdk-development dependency) and AWS Documentation MCP for serverless guidance.

Note: The following AWS MCP servers are available separately via the Full AWS MCP Server (see aws-mcp-setup skill) and are not bundled with this plugin:

• AWS Serverless MCP — SAM CLI lifecycle (init, deploy, local test)
• AWS Lambda Tool MCP — Direct Lambda invocation
• AWS Step Functions MCP — Workflow orchestration
• Amazon SNS/SQS MCP — Messaging and queue management

When to Use This Skill

Use this skill when:

• Building serverless applications with Lambda
• Designing event-driven architectures
• Implementing microservices patterns
• Creating asynchronous processing workflows
• Orchestrating multi-service transactions
• Building real-time data processing pipelines
• Implementing saga patterns for distributed transactions
• Designing for scale and resilience

AWS Well-Architected Serverless Design Principles

1. Speedy, Simple, Singular

Functions should be concise and single-purpose

// ✅ GOOD - Single purpose, focused function
export const processOrder = async (event: OrderEvent) => {
  // Only handles order processing
  const order = await validateOrder(event);
  await saveOrder(order);
  await publishOrderCreatedEvent(order);
  return { statusCode: 200, body: JSON.stringify({ orderId: order.id }) };
};

// ❌ BAD - Function does too much
export const handleEverything = async (event: any) => {
  // Handles orders, inventory, payments, shipping...
  // Too many responsibilities
};

Keep functions environmentally efficient and cost-aware:

• Minimize cold start times
• Optimize memory allocation
• Use provisioned concurrency only when needed
• Leverage connection reuse

2. Think Concurrent Requests, Not Total Requests

Design for concurrency, not volume

Lambda scales horizontally - design considerations should focus on:

• Concurrent execution limits
• Downstream service throttling
• Shared resource contention
• Connection pool sizing

// Consider concurrent Lambda executions accessing DynamoDB
const table = new dynamodb.Table(this, 'Table', {
  billingMode: dynamodb.BillingMode.PAY_PER_REQUEST, // Auto-scales with load
});

// Or with provisioned capacity + auto-scaling
const table = new dynamodb.Table(this, 'Table', {
  billingMode: dynamodb.BillingMode.PROVISIONED,
  readCapacity: 5,
  writeCapacity: 5,
});

// Enable auto-scaling for concurrent load
table.autoScaleReadCapacity({ minCapacity: 5, maxCapacity: 100 });
table.autoScaleWriteCapacity({ minCapacity: 5, maxCapacity: 100 });

3. Share Nothing

Function runtime environments are short-lived

// ❌ BAD - Relying on local file system
export const handler = async (event: any) => {
  fs.writeFileSync('/tmp/data.json', JSON.stringify(data)); // Lost after execution
};

// ✅ GOOD - Use persistent storage
export const handler = async (event: any) => {
  await s3.putObject({
    Bucket: process.env.BUCKET_NAME,
    Key: 'data.json',
    Body: JSON.stringify(data),
  });
};

State management:

• Use DynamoDB for persistent state
• Use Step Functions for workflow state
• Use ElastiCache for session state
• Use S3 for file storage

4. Assume No Hardware Affinity

Applications must be hardware-agnostic

Infrastructure can change without notice:

• Lambda functions can run on different hardware
• Container instances can be replaced
• No assumption about underlying infrastructure

Design for portability:

• Use environment variables for configuration
• Avoid hardware-specific optimizations
• Test across different environments

5. Orchestrate with State Machines, Not Function Chaining

Use Step Functions for orchestration

// ❌ BAD - Lambda function chaining
export const handler1 = async (event: any) => {
  const result = await processStep1(event);
  await lambda.invoke({
    FunctionName: 'handler2',
    Payload: JSON.stringify(result),
  });
};

// ✅ GOOD - Step Functions orchestration
const stateMachine = new stepfunctions.StateMachine(this, 'OrderWorkflow', {
  definition: stepfunctions.Chain
    .start(validateOrder)
    .next(processPayment)
    .next(shipOrder)
    .next(sendConfirmation),
});

Benefits of Step Functions:

• Visual workflow representation
• Built-in error handling and retries
• Execution history and debugging
• Parallel and sequential execution
• Service integrat