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 Lambda with TypeScript/Python, API Gateway (REST/HTTP), DynamoDB, Step Functions,...
risk: unknown
source: https://github.com/zxkane/aws-skills/tree/main/plugins/serverless-eda/skills/aws-serverless-eda
source_repo: zxkane/aws-skills
source_type: community
date_added: 2026-07-01
license: MIT
license_source: https://github.com/zxkane/aws-skills/blob/main/LICENSE
---

# 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**

```typescript
// ✅ 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

```typescript
// 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**

```typescript
// ❌ 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**

```typescript
// ❌ 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 integrations without code

### 6. Use Events to Trigger Transactions

**Event-driven over synchronous request/response**

```typescript
// Pattern: Event-driven processing
const bucket = new s3.Bucket(this, 'DataBucket');

bucket.addEventNotification(
  s3.EventType.OBJECT_CREATED,
  new s3n.LambdaDestination(processFunction),
  { prefix: 'uploads/' }
);

// Pattern: EventBridge integration
const rule = new events.Rule(this, 'OrderRule', {
  eventPattern: {
    source: ['orders'],
    detailType: ['OrderPlaced'],
  },
});

rule.addTarget(new targets.LambdaFunction(processOrderFunction));
```

**Benefits**:
- Loose coupling between services
- Asynchronous processing
- Better fault tolerance
- Independent scaling

### 7. Design for Failures and Duplicates

**Operations must be idempotent**

```typescript
// ✅ GOOD - Idempotent operation
export const handler = async (event: SQSEvent) => {
  for (const record of event.Records) {
    const orderId = JSON.parse(record.body).orderId;

    // Check if already processed (idempotency)
    const existing = await dynamodb.getItem({
      TableName: process.env.TABLE_NAME,
      Key: { orderId },
    });

    if (existing.Item) {
      console.log('Order already processed:', orderId);
      continue; // Skip duplicate
    }

    // Process order
    await processOrder(orderId);

    // Mark as processed
    await dynamodb.putItem({
      TableName: process.env.TABLE_NAME,
      Item: { orderId, processedAt: Date.now() },
    });
  }
};
```

**Implement retry logic with exponential backoff**:
```typescript
async function withRetry<T>(fn: () => Promise<T>, maxRetries = 3): Promise<T> {
  for (let i = 0; i < maxRetries; i++) {
    try {
      return await fn();
    } catch (error) {
      if (i === maxRetries - 1) throw error;
      await new Promise(resolve => setTimeout(resolve, Math.pow(2, i) * 1000));
    }
  }
  throw new Error('Max retries exceeded');
}
```

## Architecture Patterns

For detailed implementation patterns with full code examples, see the reference documentation:

### Event-Driven Architecture Patterns
**File**: `references/eda-patterns.md`
- Event Router with EventBridge (custom event bus, schema registry, rule-based routing)
- Queue-Based Processing with SQS (standard/FIFO, DLQ, Lambda consumers)
- Pub/Sub Fan-Out with SNS + SQS (multi-consumer, filtering)
- Saga Pattern with Step Functions (distributed transactions, compensating actions)
- Event Sourcing with DynamoDB Streams (append-only event store, projections)

### Serverless Architecture Patterns
**File**: `references/serverless-patterns.md`
- API-Driven Microservices (REST API + Lambda backend)
- Stream Processing with Kinesis (real-time, batch windowing, bisect on error)
- Async Task Processing with SQS (background jobs, concurrency control)
- Scheduled Jobs with EventBridge (cron/rate schedules)
- Webhook Processing (signature validation, async queue forwarding)

> **Important**: When using CDK code examples from references, avoid hardcoding resource names (e.g., `restApiName`, `eventBusName`). Let CDK generate unique names automatically to enable reusability and parallel deployments. See `aws-cdk-development` skill for details.

## Best Practices

### Error Handling

**Implement comprehensive error handling**:

```typescript
export const handler = async (event: SQSEvent) => {
  const failures: SQSBatchItemFailure[] = [];

  for (const record of event.Records) {
    try {
      await processRecord(record);
    } catch (error) {
      console.error('Failed to process record:', record.messageId, error);
      failures.push({ itemIdentifier: record.messageId });
    }
  }

  // Return partial batch failures for retry
  return { batchItemFailures: failures };
};
```

### Dead Letter Queues

**Always configure DLQs for error handling**:

```typescript
const dlq = new sqs.Queue(this, 'DLQ', {
  retentionPeriod: Duration.days(14),
});

const queue = new sqs.Queue(this, 'Queue', {
  deadLetterQueue: {
    queue: dlq,
    maxReceiveCount: 3,
  },
});

// Monitor DLQ depth
new cloudwatch.Alarm(this, 'DLQAlarm', {
  metric: dlq.metricApproximateNumberOfMessagesVisible(),
  threshold: 1,
  evaluationPeriods: 1,
  alarmDescription: 'Messages in DLQ require attention',
});
```

### Observability

**Enable tracing and monitoring**:

```typescript
new NodejsFunction(this, 'Function', {
  entry: 'src/handler.ts',
  tracing: lambda.Tracing.ACTIVE, // X-Ray tracing
  environment: {
    POWERTOOLS_SERVICE_NAME: 'order-service',
    POWERTOOLS_METRICS_NAMESPACE: 'MyApp',
    LOG_LEVEL: 'INFO',
  },
});
```

## Using MCP Servers Effectively

Use the CDK MCP server (via `aws-cdk-development` dependency) for construct recommendations and CDK-specific guidance when building serverless infrastructure.

Use AWS Documentation MCP to verify service features, regional availability, and API specifications before implementing.

## Additional Resources

This skill includes comprehensive reference documentation based on AWS best practices:

- **Serverless Patterns**: `references/serverless-patterns.md`
  - Core serverless architectures and API patterns
  - Data processing and integration patterns
  - Orchestration with Step Functions
  - Anti-patterns to avoid

- **Event-Driven Architecture Patterns**: `references/eda-patterns.md`
  - Event routing and processing patterns
  - Event sourcing and saga patterns
  - Idempotency and error handling
  - Message ordering and deduplication

- **Security Best Practices**: `references/security-best-practices.md`
  - Shared responsibility model
  - IAM least privilege patterns
  - Data protection and encryption
  - Network security with VPC

- **Observability Best Practices**: `references/observability-best-practices.md`
  - Three pillars: metrics, logs, traces
  - Structured logging with Lambda Powertools
  - X-Ray distributed tracing
  - CloudWatch alarms and dashboards

- **Performance Optimization**: `references/performance-optimization.md`
  - Cold start optimization techniques
  - Memory and CPU optimization
  - Package size reduction
  - Provisioned concurrency patterns

- **Deployment Best Practices**: `references/deployment-best-practices.md`
  - CI/CD pipeline design
  - Testing strategies (unit, integration, load)
  - Deployment strategies (canary, blue/green)
  - Rollback and safety mechanisms

**External Resources**:
- **AWS Well-Architected Serverless Lens**: https://docs.aws.amazon.com/wellarchitected/latest/serverless-applications-lens/
- **ServerlessLand.com**: Pre-built serverless patterns
- **AWS Serverless Workshops**: https://serverlessland.com/learn?type=Workshops

For detailed implementation patterns, anti-patterns, and code examples, refer to the comprehensive references in the skill directory.

## Limitations

- Use this skill only when the task clearly matches its upstream source and local project context.
- Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
- Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.