Retries, DLQs, and Lambda destinations

1. Handling the event lifecycle: retries, DLQs and destinations

In this video, you'll learn what happens when event processing fails. We'll compare synchronous errors with asynchronous retries, then use DLQs and destinations to route outcomes instead of losing events.

2. The event lifecycle at a glance

Think of each event as a small workflow. Lambda invokes your handler, and the handler either succeeds or fails. When it fails, retries and routing decide what happens next.

3. Two ways failures show up

With synchronous invocation, the caller waits and receives an error response. With asynchronous delivery, the caller is acknowledged first and Lambda retries in the background. The failure handling path depends on the invocation mode.

4. Retries are normal

Retries are often a feature, not a bug. A transient failure might succeed on the next attempt. But retries can also cause duplicate processing, so your handler design needs to account for it.

5. Retries over time

Retries can recover from transient issues, but the same event may run multiple times. This is why idempotency and clear error handling are essential in event-driven Lambda designs.

6. When retries are dangerous

Retries are risky when work is not idempotent, like charging a card or sending an email. Use idempotency keys and safe updates so duplicates do not cause harm.

7. DLQ (Dead-Letter Queue)

A DLQ is a dead-letter queue: a safe place for events that still fail after retries, often an SQS queue, AWS's managed message queue. You inspect the payload, fix the issue, and re-drive.

8. DLQ vs destinations

A DLQ captures failed events after retries. Destinations route outcomes on success or on failure. You can use a DLQ for investigation, and destinations to build explicit success and failure paths.

9. Destinations: success and failure routes

Destinations are like delivery receipts. On success, send a result to onSuccess. On failure, send details to onFailure. This makes the next step explicit.

10. Tuning retry policy

You can tune how many times Lambda retries and how long an event remains eligible for processing. More retries improve reliability but can increase duplicates and delay. Limiting event age avoids processing stale data.

11. Maximum event age: an expiration date

Maximum event age is an expiration policy. If an event is too old, processing it may be pointless. This is a trade-off: fewer late events, more timely behavior.

12. Observability: where to look

When something fails, logs answer what happened. When you need trends, metrics answer how often it is happening. For Lambda, CloudWatch gives you both logs and metrics, and alarms help you catch spikes quickly.

13. What to do with failed events

Failure routing is only useful if you act on it. Inspect the payload and error, fix the root cause, and then re-drive the event. Finally, monitor errors and throughput to confirm the system is stable.

14. Key takeaways

Reliability comes from retries, routing, and observability. Synchronous errors reach the caller. Asynchronous errors need retries plus DLQs or destinations so failures are visible.

15. Let's practice!

Let's practice what we've learned with some exercises!

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