---
name: aws-serverless-eda-f008433c085a
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, EventBridge, SQS, SNS, and serverless patterns. Essential when user mentions serverless, Lambda, API Gateway, event-driven, async processing, queues, pub/sub, or wants to build scalable serverless applications with AWS best practices.
---

# 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.

## Integrated MCP Servers

This skill includes 5 MCP servers for serverless development:

### AWS Documentation MCP Server
**When to use**: Always verify AWS service information before implementation
- Search AWS documentation for latest features and best practices
- Check regional availability of AWS services
- Verify service limits and quotas
- Confirm API specifications and parameters
- Access up-to-date AWS service information

### AWS Serverless MCP Server
**Purpose**: Complete serverless application lifecycle with SAM CLI
- Initialize new serverless applications
- Deploy serverless applications
- Test Lambda functions locally
- Generate SAM templates
- Manage serverless application lifecycle

### AWS Lambda Tool MCP Server
**Purpose**: Execute Lambda functions as tools
- Invoke Lambda functions directly
- Test Lambda integrations
- Execute workflows requiring private resource access
- Run Lambda-based automation

### AWS Step Functions MCP Server
**Purpose**: Execute complex workflows and orchestration
- Create and manage state machines
- Execute workflow orchestrations
- Handle distributed transactions
- Implement saga patterns
- Coordinate microservices

### Amazon SNS/SQS MCP Server
**Purpose**: Event-driven messaging and queue management
- Publish messages to SNS topics
- Send/receive messages from SQS queues
- Manage event-driven communication
- Implement pub/sub patterns
- Handle asynchronous processing

## 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');
}
```

## Event-Driven Architecture Patterns

### Pattern 1: Event Router (EventBridge)

Use EventBridge for event routing and filtering:

```typescript
// Create custom event bus
const eventBus = new events.EventBus(this, 'AppEventBus', {
  eventBusName: 'application-events',
});

// Define event schema
const schema = new events.Schema(this, 'OrderSchema', {
  schemaName: 'OrderPlaced',
  definition: events.SchemaDefinition.fromInline({
    openapi: '3.0.0',
    info: { version: '1.0.0', title: 'Order Events' },
    paths: {},
    components: {
      schemas: {
        OrderPlaced: {
          type: 'object',
          properties: {
            orderId: { type: 'string' },
            customerId: { type: 'string' },
            amount: { type: 'number' },
          },
        },
      },
    },
  }),
});

// Create rules for different consumers
new events.Rule(this, 'ProcessOrderRule', {
  eventBus,
  eventPattern: {
    source: ['orders'],
    detailType: ['OrderPlaced'],
  },
  targets: [new targets.LambdaFunction(processOrderFunction)],
});

new events.Rule(this, 'NotifyCustomerRule', {
  eventBus,
  eventPattern: {
    source: ['orders'],
    detailType: ['OrderPlaced'],
  },
  targets: [new targets.LambdaFunction(notifyCustomerFunction)],
});
```

### Pattern 2: Queue-Based Processing (SQS)

Use SQS for reliable asynchronous processing:

```typescript
// Standard queue for at-least-once delivery
const queue = new sqs.Queue(this, 'ProcessingQueue', {
  visibilityTimeout: Duration.seconds(300),
  retentionPeriod: Duration.days(14),
  deadLetterQueue: {
    queue: dlq,
    maxReceiveCount: 3,
  },
});

// FIFO queue for ordered processing
const fifoQueue = new sqs.Queue(this, 'OrderedQueue', {
  fifo: true,
  contentBasedDeduplication: true,
  deduplicationScope: sqs.DeduplicationScope.MESSAGE_GROUP,
});

// Lambda consumer
new lambda.EventSourceMapping(this, 'QueueConsumer', {
  target: processingFunction,
  eventSourceArn: queue.queueArn,
  batchSize: 10,
  maxBatchingWindow: Duration.seconds(5),
});
```

### Pattern 3: Pub/Sub (SNS + SQS Fan-Out)

Implement fan-out pattern for multiple consumers:

```typescript
// Create SNS topic
const topic = new sns.Topic(this, 'OrderTopic', {
  displayName: 'Order Events',
});

// Multiple SQS queues subscribe to topic
const inventoryQueue = new sqs.Queue(this, 'InventoryQueue');
const shippingQueue = new sqs.Queue(this, 'ShippingQueue');
const analyticsQueue = new sqs.Queue(this, 'AnalyticsQueue');

topic.addSubscription(new subscriptions.SqsSubscription(inventoryQueue));
topic.addSubscription(new subscriptions.SqsSubscription(shippingQueue));
topic.addSubscription(new subscriptions.SqsSubscription(analyticsQueue));

// Each queue has its own Lambda consumer
new lambda.EventSourceMapping(this, 'InventoryConsumer', {
  target: inventoryFunction,
  eventSourceArn: inventoryQueue.queueArn,
});
```

### Pattern 4: Saga Pattern with Step Functions

Implement distributed transactions:

```typescript
const reserveFlight = new tasks.LambdaInvoke(this, 'ReserveFlight', {
  lambdaFunction: reserveFlightFunction,
  outputPath: '$.Payload',
});

const reserveHotel = new tasks.LambdaInvoke(this, 'ReserveHotel', {
  lambdaFunction: reserveHotelFunction,
  outputPath: '$.Payload',
});

const processPayment = new tasks.LambdaInvoke(this, 'ProcessPayment', {
  lambdaFunction: processPaymentFunction,
  outputPath: '$.Payload',
});

// Compensating transactions
const cancelFlight = new tasks.LambdaInvoke(this, 'CancelFlight', {
  lambdaFunction: cancelFlightFunction,
});

const cancelHotel = new tasks.LambdaInvoke(this, 'CancelHotel', {
  lambdaFunction: cancelHotelFunction,
});

// Define saga with compensation
const definition = reserveFlight
  .next(reserveHotel)
  .next(processPayment)
  .addCatch(cancelHotel.next(cancelFlight), {
    resultPath: '$.error',
  });

new stepfunctions.StateMachine(this, 'BookingStateMachine', {
  definition,
  timeout: Duration.minutes(5),
});
```

### Pattern 5: Event Sourcing

Store events as source of truth:

```typescript
// Event store with DynamoDB
const eventStore = new dynamodb.Table(this, 'EventStore', {
  partitionKey: { name: 'aggregateId', type: dynamodb.AttributeType.STRING },
  sortKey: { name: 'version', type: dynamodb.AttributeType.NUMBER },
  stream: dynamodb.StreamViewType.NEW_IMAGE,
});

// Lambda function stores events
export const handleCommand = async (event: any) => {
  const { aggregateId, eventType, eventData } = event;

  // Get current version
  const items = await dynamodb.query({
    TableName: process.env.EVENT_STORE,
    KeyConditionExpression: 'aggregateId = :id',
    ExpressionAttributeValues: { ':id': aggregateId },
    ScanIndexForward: false,
    Limit: 1,
  });

  const nextVersion = items.Items?.[0]?.version + 1 || 1;

  // Append new event
  await dynamodb.putItem({
    TableName: process.env.EVENT_STORE,
    Item: {
      aggregateId,
      version: nextVersion,
      eventType,
      eventData,
      timestamp: Date.now(),
    },
  });
};

// Projections read from event stream
eventStore.grantStreamRead(projectionFunction);
```

## Serverless Architecture Patterns

### Pattern 1: API-Driven Microservices

REST APIs with Lambda backend:

```typescript
const api = new apigateway.RestApi(this, 'Api', {
  restApiName: 'microservices-api',
  deployOptions: {
    throttlingRateLimit: 1000,
    throttlingBurstLimit: 2000,
    tracingEnabled: true,
  },
});

// User service
const users = api.root.addResource('users');
users.addMethod('GET', new apigateway.LambdaIntegration(getUsersFunction));
users.addMethod('POST', new apigateway.LambdaIntegration(createUserFunction));

// Order service
const orders = api.root.addResource('orders');
orders.addMethod('GET', new apigateway.LambdaIntegration(getOrdersFunction));
orders.addMethod('POST', new apigateway.LambdaIntegration(createOrderFunction));
```

### Pattern 2: Stream Processing

Real-time data processing with Kinesis:

```typescript
const stream = new kinesis.Stream(this, 'DataStream', {
  shardCount: 2,
  retentionPeriod: Duration.days(7),
});

// Lambda processes stream records
new lambda.EventSourceMapping(this, 'StreamProcessor', {
  target: processFunction,
  eventSourceArn: stream.streamArn,
  batchSize: 100,
  maxBatchingWindow: Duration.seconds(5),
  parallelizationFactor: 10,
  startingPosition: lambda.StartingPosition.LATEST,
  retryAttempts: 3,
  bisectBatchOnError: true,
  onFailure: new lambdaDestinations.SqsDestination(dlq),
});
```

### Pattern 3: Async Task Processing

Background job processing:

```typescript
// SQS queue for tasks
const taskQueue = new sqs.Queue(this, 'TaskQueue', {
  visibilityTimeout: Duration.minutes(5),
  receiveMessageWaitTime: Duration.seconds(20), // Long polling
  deadLetterQueue: {
    queue: dlq,
    maxReceiveCount: 3,
  },
});

// Lambda worker processes tasks
const worker = new lambda.Function(this, 'TaskWorker', {
  // ... configuration
  reservedConcurrentExecutions: 10, // Control concurrency
});

new lambda.EventSourceMapping(this, 'TaskConsumer', {
  target: worker,
  eventSourceArn: taskQueue.queueArn,
  batchSize: 10,
  reportBatchItemFailures: true, // Partial batch failure handling
});
```

### Pattern 4: Scheduled Jobs

Periodic processing with EventBridge:

```typescript
// Daily cleanup job
new events.Rule(this, 'DailyCleanup', {
  schedule: events.Schedule.cron({ hour: '2', minute: '0' }),
  targets: [new targets.LambdaFunction(cleanupFunction)],
});

// Process every 5 minutes
new events.Rule(this, 'FrequentProcessing', {
  schedule: events.Schedule.rate(Duration.minutes(5)),
  targets: [new targets.LambdaFunction(processFunction)],
});
```

### Pattern 5: Webhook Processing

Handle external webhooks:

```typescript
// API Gateway endpoint for webhooks
const webhookApi = new apigateway.RestApi(this, 'WebhookApi', {
  restApiName: 'webhooks',
});

const webhook = webhookApi.root.addResource('webhook');
webhook.addMethod('POST', new apigateway.LambdaIntegration(webhookFunction, {
  proxy: true,
  timeout: Duration.seconds(29), // API Gateway max
}));

// Lambda handler validates and queues webhook
export const handler = async (event: APIGatewayProxyEvent) => {
  // Validate webhook signature
  const isValid = validateSignature(event.headers, event.body);
  if (!isValid) {
    return { statusCode: 401, body: 'Invalid signature' };
  }

  // Queue for async processing
  await sqs.sendMessage({
    QueueUrl: process.env.QUEUE_URL,
    MessageBody: event.body,
  });

  // Return immediately
  return { statusCode: 202, body: 'Accepted' };
};
```

## 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

### AWS Serverless MCP Usage

**Lifecycle management**:
- Initialize new serverless projects
- Generate SAM templates
- Deploy applications
- Test locally before deployment

### Lambda Tool MCP Usage

**Function execution**:
- Test Lambda functions directly
- Execute automation workflows
- Access private resources
- Validate integrations

### Step Functions MCP Usage

**Workflow orchestration**:
- Create state machines for complex workflows
- Execute distributed transactions
- Implement saga patterns
- Coordinate microservices

### SNS/SQS MCP Usage

**Messaging operations**:
- Test pub/sub patterns
- Send test messages to queues
- Validate event routing
- Debug message processing

## 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.


---
Source attribution: Activer007
Original project: https://github.com/Activer007/ordinary-claude-skills/blob/e3e1b3d55f9a132a68d242040d23048a7ba8f85c/skills_all/aws-skills/skills/aws-serverless-eda/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2025 Mengxin Zhu

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: Activer007
Original project: https://github.com/Activer007/ordinary-claude-skills/blob/e3e1b3d55f9a132a68d242040d23048a7ba8f85c/skills_all/aws-skills/skills/aws-serverless-eda/SKILL.md
Attribution basis: Source repository record

Fields of work: Development & Engineering, Product Management
Roles: Backend Developer, Data Engineer, DevOps / SRE, Product Manager, Technical Product Manager
Specialties: API, Backend
Tools: AWS
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: ed6f745709ff7bef0cfc1f8a1878d6c0631e0968c6eb4acc54b99e220d0a78cd