Event-driven architecture essentials

1. Event-driven architecture essentials

Welcome back. You know the Lambda flow: event in, handler runs, outcome out. Now let's focus on event sources, payloads, and invocation mode.

2. Recap: one Lambda mental model

Let's start with a quick recap. An event source like S3 or SQS sends a JSON payload. Lambda passes it to your handler, your code produces an outcome, and logs are where you debug.

3. Events are messages

An event is a JSON message that says something happened. Like a doorbell, it tells your handler to wake up, extract the fields it needs, and take action.

4. Common event sources in AWS

Now let's look at some common event sources. Amazon S3 triggers events on uploads. Amazon SQS is a managed queue that delivers messages. DynamoDB Streams produces a change log. Each produces a different JSON payload.

5. Synchronous vs asynchronous invocation

Synchronous invocation is like a phone call: the caller waits for a result. Asynchronous invocation is like voicemail: the caller gets an acknowledgment and the event is processed later.

6. Who sees the error?

With synchronous invocations, the caller receives the error. With asynchronous delivery, Lambda retries and can route failures, so you debug through logs and failure targets.

7. Payloads are contracts

Think of each payload as a contract: the sender decides the shape, and your handler needs to know where to find the fields. Payload shapes vary, but your job stays the same: extract what you need, validate it, process it, and log.

8. Example payload: SQS message event

Let's look at a real example: here's what an SQS event looks like when it arrives. This is a simplified version: Records is the batch, body is a string, and messageId helps you trace and deduplicate processing.

9. Walkthrough: iterate through Records

Start by reading Records with a safe default, then loop through each record and extract the body. Log what matters, and return your response.

10. Walkthrough: parse JSON body safely

The body field is just a string, so you need to parse it. Read it with a safe default, convert it with json.loads into a Python dict, then extract order_id and return JSON with json.dumps.

11. Defensive parsing checklist

Before we move on, here's a checklist for parsing any event: log the event shape when learning a new source, use get with defaults for optional fields, validate required fields and return clear errors, and handle empty batches and missing keys.

12. Design for retries and duplicates

What happens if the same event arrives twice? Many event sources use at-least-once delivery, so duplicates can happen. Design handlers to be idempotent so processing the same event twice stays correct.

13. Idempotency in practice

So how do you implement idempotency? Choose a unique key, like messageId or order_id. Store each processed key in DynamoDB. When a new event arrives, check if the key exists. If it does, skip the work.

14. Key takeaways

Events arrive as JSON from AWS services. Invocation mode changes where errors appear. Payloads vary, so parse and validate defensively. Assume retries and duplicates. Keep these principles in mind as you build event-driven applications. They'll save you from debugging headaches later.

15. Let's practice!

Now, let's practice!

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