Error Handling, Retries & Dead-Letter Queues
Build robust Lambda functions by understanding how errors propagate, how retries work per invocation type, and how dead-letter queues capture failures.
Error Handling, Retries & Dead-Letter Queues is a free Serverless Backend with AWS Lambda & API Gateway lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Serverless Backend with AWS Lambda & API Gateway learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Errors in Serverless Functions
When a function throws or times out, the platform treats it as a failed invocation. How that failure is handled depends on how the function was invoked.
- Synchronous: error returns to the caller
- Asynchronous: platform retries automatically
- Stream/poll: behavior depends on the source
Synchronous Error Handling
For synchronous calls (like an API request) the error is returned immediately to the caller. The caller, such as API Gateway, decides how to map it to an HTTP status.
Asynchronous Retries
For asynchronous invocations the platform automatically retries failed events a couple of times with delay before giving up. Your code must be safe to run more than once.
Idempotency
Because retries can re-run an event, functions should be idempotent: processing the same event twice produces the same result without duplicate side effects.
def handler(event, context):
key = event["id"]
if already_processed(key):
return "skip"
process(key)
mark_processed(key)
return "ok"Try/Except in the Handler
Catch expected errors and respond gracefully; let truly unexpected errors bubble up so the platform can retry or record them.
def handler(event, context):
try:
return do_work(event)
except ValidationError as e:
return {"statusCode": 400, "body": str(e)}Dead-Letter Queues
A dead-letter queue (DLQ) captures events that still fail after all retries, so they are not lost. You can inspect and reprocess them later.
- Attach an SQS queue or SNS topic as the DLQ
- Failed events land there with metadata
Configuring a DLQ
You point the function at a DLQ target. After exhausting retries, the platform delivers the failed event there instead of dropping it.
aws lambda update-function-configuration \
--function-name worker \
--dead-letter-config TargetArn=arn:aws:sqs:...:failed-eventsDestinations: Success and Failure
Beyond DLQs, destinations route the result of async invocations on success or failure to another service, with richer context than a DLQ provides.
Handling Stream Failures
For stream sources (like a queue or stream), a failing batch can block progress. Configure batch bisection or a maximum retry age so a single poison message does not stall the whole stream.
Timeouts vs Errors
A timeout is a kind of failure: the function did not finish in time. Set timeouts realistically and instrument long operations so you can tell timeouts apart from thrown errors.
Observability for Failures
Log errors with context, emit metrics for failure counts, and alarm on DLQ depth. A growing DLQ is an early signal that something is systematically broken.
Quick Check
Test your error-handling understanding.
Recap
You learned robust Lambda error handling: how errors propagate per invocation type, why idempotency matters with retries, how to use try/except wisely, and how dead-letter queues and destinations capture failures so events are never silently lost.
Frequently asked questions
Is the “Error Handling, Retries & Dead-Letter Queues” lesson free?
Yes — the full text of “Error Handling, Retries & Dead-Letter Queues” is free to read here on the web, and the Serverless Backend with AWS Lambda & API Gateway course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Serverless Backend with AWS Lambda & API Gateway course, upgrade to CoddyKit PRO.
What will I learn in “Error Handling, Retries & Dead-Letter Queues”?
Build robust Lambda functions by understanding how errors propagate, how retries work per invocation type, and how dead-letter queues capture failures. You practise Serverless Backend with AWS Lambda & API Gateway with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Serverless Backend with AWS Lambda & API Gateway?
No prior experience is required. Serverless Backend with AWS Lambda & API Gateway on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Error Handling, Retries & Dead-Letter Queues” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Serverless Backend with AWS Lambda & API Gateway lesson?
Yes. Every Serverless Backend with AWS Lambda & API Gateway lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Lambda Runtime and Handler
- Environment Variables and Layers
- Logging and Monitoring with CloudWatch
- Error Handling, Retries & Dead-Letter Queues