
event-driven-serverless-systems
Build event-driven architectures on AWS serverless infrastructure. Designs event flows, integrates Lambda with event sources, and manages distributed systems.
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Works with every agent the skills CLI supports.
npx skills add https://github.com/qodex-ai/ai-agent-skills --skill event-driven-serverless-systems- 01
Install
Run the command in your project. The CLI asks which agents to install for.
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Describe the task
Ask your agent for something this skill covers. It loads event-driven-serverless-systems automatically when relevant.
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Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
CRITICAL: This skill requires AWS MCP tools for accurate, up-to-date AWS information.
Before Answering AWS Questions
-
Always verify using AWS MCP tools (if available):
mcp__aws-mcp__aws___search_documentationormcp__*awsdocs*__aws___search_documentation- Search AWS docsmcp__aws-mcp__aws___read_documentationormcp__*awsdocs*__aws___read_documentation- Read specific pagesmcp__aws-mcp__aws___get_regional_availability- Check service availability
-
If AWS MCP tools are unavailable:
- Guide user to configure AWS MCP: See AWS MCP Setup Guide
- Help determine which option fits their environment:
- Has uvx + AWS credentials → Full AWS MCP Server
- No Python/credentials → AWS Documentation MCP (no auth)
- If cannot determine → Ask user which option to use
Serverless MCP Servers
This skill can leverage serverless-specific MCP servers for enhanced development workflows:
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
// ✅ 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 integrations without code
6. Use Events to Trigger Transactions
Event-driven over synchronous request/response
// 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
// ✅ 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:
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:
// 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:
// 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:
// 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:
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:
// 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:
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:
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:
// 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:
// 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:
// 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:
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:
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:
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.
FAQ
What does the event-driven-serverless-systems skill do?
Build event-driven architectures on AWS serverless infrastructure. Designs event flows, integrates Lambda with event sources, and manages distributed systems.
How do I install event-driven-serverless-systems?
Run npx skills add https://github.com/qodex-ai/ai-agent-skills --skill event-driven-serverless-systems in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/event-driven-serverless-systems/ (personal) or .claude/skills/event-driven-serverless-systems/ (project).
Which AI agents can use event-driven-serverless-systems?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is event-driven-serverless-systems safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains event-driven-serverless-systems?
It is published by qodex-ai in qodex-ai/ai-agent-skills. It has 135 recorded installs.
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