Building Your First Event-driven Application on AWS

Event-driven architecture (EDA) has become the backbone of modern cloud applications, and for good reason. It enables loose coupling, better scalability, and improved fault tolerance. If you’re looking to build resilient applications on AWS, event-driven patterns should be in your toolkit.

Today, I’ll walk you through building your first event-driven application using a powerful combination of AWS services: API Gateway → Lambda → SQS → Lambda → SNS. We’ll use a real-world example that you can relate to and potentially implement in your own projects.

Our Use Case: Order Processing System

Let’s build an order processing system for an e-commerce platform. Here’s what needs to happen when a customer places an order:

1. Customer submits an order via a web/mobile app

2. The order gets validated and initially processed

3. Various downstream systems need to be notified (inventory, payment, shipping, customer notifications)

4. Each system should process the order independently without blocking others

This is a perfect scenario for event-driven architecture because we have multiple independent processes that need to react to the same event (order creation) without tightly coupling them together.

The Architecture Flow

1. API Gateway: The Front Door

API Gateway serves as our entry point, receiving HTTP POST requests from the frontend application when customers place orders. It provides:

• Authentication and authorization - ensuring only valid requests get through

• Rate limiting - protecting your backend from traffic spikes

• Request validation - catching malformed requests before they reach your Lambda

• Monitoring and logging - giving you visibility into your API usage

When a customer clicks “Place Order,” their request hits an endpoint like POST /orders on your API Gateway.

2. First Lambda: Order Validator and Publisher

The first Lambda function acts as your order processor. Its responsibilities include:

• Validating the order data - checking required fields, formats, and business rules

• Performing initial processing - calculating totals, applying discounts, generating order IDs

• Publishing to SQS - sending the validated order to a queue for further processing

This Lambda should be fast and focused. It’s synchronous (the customer is waiting for a response), so you want to do the minimum viable processing and quickly acknowledge the order.

3. SQS: The Reliable Message Queue

Simple Queue Service acts as a buffer between your initial order processing and downstream systems. This is where the magic of decoupling happens:

• Durability - if your downstream Lambda fails, messages don’t get lost

• Retry logic - failed messages can be retried automatically

• Scaling buffer - handles traffic spikes by queuing messages when downstream systems are busy

• Dead letter queues - captures messages that fail repeatedly for manual investigation

Your order data sits safely in SQS, waiting to be processed by the next component.

4. Second Lambda: Order Orchestrator

This Lambda function is triggered by messages arriving in your SQS queue. It’s responsible for:

• Enriching order data - adding customer details, product information, or other context

• Business logic execution - inventory checks, fraud detection, or other complex processing

• Event publishing - sending notifications to multiple downstream systems via SNS

This function can take more time since it’s asynchronous - the customer isn’t waiting for it to complete.

5. SNS: The Event Broadcaster

Simple Notification Service is your event distribution hub. When your second Lambda publishes an “Order Processed” event to SNS, multiple subscribers can react:

• Inventory service - reserves items and updates stock levels

• Payment service - processes payment and handles billing

• Shipping service - calculates shipping costs and prepares logistics

• Email service - sends order confirmation to the customer

• Analytics service - updates dashboards and reports

Each subscriber processes the order independently. If the email service is down, inventory updates still happen. If payment processing is slow, it doesn’t block shipping calculations.

Why This Architecture Works

Resilience Through Decoupling

Each component can fail independently without bringing down the entire system. If your email service is having issues, orders still get processed, inventory gets updated, and payments go through.

Independent Scaling

Your order validation Lambda might need different scaling settings than your order processing Lambda. API Gateway can handle thousands of concurrent requests while your SQS queue smooths out the load to downstream systems.

Easy Testing and Development

You can test each component in isolation. Want to test your inventory service? Just publish a test message to SNS. Need to debug order processing? Check the SQS queue for pending messages.

Monitoring and Observability

Each service provides its own metrics and logs. You can track API Gateway response times, Lambda execution duration, SQS queue depth, and SNS delivery success rates independently.

Real-World Considerations

Message Design

Design your messages to be self-contained and versioned. Include all the information downstream services need to process the order without making additional API calls.

Error Handling

Implement proper error handling at each stage. Use dead letter queues for messages that fail repeatedly, and set up CloudWatch alarms to notify you of processing issues.

Cost Optimization

This architecture follows AWS’s pay-per-use model beautifully. You only pay for API calls processed, Lambda executions, messages queued, and notifications sent.

Security

Each service can have its own IAM permissions following the principle of least privilege. Your Lambda functions only get access to the specific SQS queues and SNS topics they need.

Conclusion

Start simple with this architecture. Begin with basic order validation and a single SNS subscriber. As you get comfortable with the pattern, add more sophisticated processing logic and additional event subscribers.

The beauty of event-driven architecture is that it grows with your needs. Today you might have three services subscribing to order events. Next month you might add analytics, fraud detection, or third-party integrations - all without changing your core order processing flow.

Event-driven architecture isn’t just a technical pattern; it’s a mindset shift toward building systems that are inherently scalable, resilient, and maintainable. Start with this foundation, and you’ll be amazed at how naturally your AWS applications begin to scale.

If you’re intrigued by the concepts of AWS Serverless, I invite you to explore my book, Mastering Event-Driven Microservices in AWS. This practical guide equips you with the knowledge and skills to design, build, and operate resilient, scalable, and fault-tolerant systems using AWS Serverless services.

Happy reading!