Monitoring and Debugging Lambda Functions
Learn how to observe, log, trace, and troubleshoot AWS Lambda functions in production using CloudWatch, X-Ray, and structured logging.
Monitoring and Debugging Lambda Functions is a free AWS for Backend Developers (EC2, S3, RDS, Lambda) 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 AWS for Backend Developers (EC2, S3, RDS, Lambda) learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Why Observability Matters
Serverless functions are short-lived and invisible — you cannot SSH into them. Observability is how you understand what your Lambda is doing.
The three pillars are logs, metrics, and traces.
Logging with CloudWatch
Anything your function writes to stdout/stderr goes to CloudWatch Logs automatically. Each function gets its own log group.
exports.handler = async (event) => {
console.log('Received event:', JSON.stringify(event));
return { statusCode: 200, body: 'OK' };
};Structured Logging
Plain text logs are hard to query. Log JSON objects so you can filter on fields later.
- Include a requestId
- Include severity and context
console.log(JSON.stringify({
level: 'INFO',
requestId: context.awsRequestId,
message: 'Order processed',
orderId: 42
}));Built-in Lambda Metrics
Lambda publishes metrics to CloudWatch out of the box:
- Invocations — how often it ran
- Errors — failed executions
- Duration — execution time
- Throttles — rejected due to concurrency limits
Setting Alarms on Errors
Create a CloudWatch alarm so you get notified when error rates spike, instead of finding out from angry users.
aws cloudwatch put-metric-alarm \
--alarm-name lambda-errors \
--metric-name Errors \
--namespace AWS/Lambda \
--threshold 1 \
--comparison-operator GreaterThanThreshold \
--evaluation-periods 1Distributed Tracing with X-Ray
AWS X-Ray traces a request as it flows through Lambda, DynamoDB, S3, and other services. It reveals where time is spent and which downstream call is slow.
Enable Active tracing in the function configuration.
Cold Starts
A cold start happens when Lambda spins up a fresh execution environment. It adds latency to the first request.
Watch Init Duration in your logs to measure cold start impact.
Reducing Cold Starts
Ways to reduce cold start pain:
- Use Provisioned Concurrency to keep environments warm
- Keep deployment packages small
- Avoid heavy initialization at module load
Handling Errors Gracefully
Wrap risky code in try/catch and return meaningful errors. Unhandled exceptions count as Lambda errors and may trigger retries.
exports.handler = async (event) => {
try {
return await process(event);
} catch (err) {
console.error('Processing failed', err);
throw err;
}
};Dead Letter Queues
For asynchronous invocations that keep failing, configure a Dead Letter Queue (DLQ) using SQS or SNS. Failed events land there so you can inspect and reprocess them.
Putting It Together
A well-monitored Lambda has:
- Structured JSON logs
- CloudWatch alarms on Errors and Duration
- X-Ray tracing enabled
- A DLQ for failed async events
Quick Check
Test your debugging knowledge.
Recap
You learned to monitor and debug Lambda:
- CloudWatch Logs capture stdout/stderr
- Metrics and alarms alert on errors
- X-Ray traces distributed calls
- DLQs capture failed async events
Good observability turns invisible serverless failures into solvable problems.
Frequently asked questions
Is the “Monitoring and Debugging Lambda Functions” lesson free?
Yes — the full text of “Monitoring and Debugging Lambda Functions” is free to read here on the web, and the AWS for Backend Developers (EC2, S3, RDS, Lambda) 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 AWS for Backend Developers (EC2, S3, RDS, Lambda) course, upgrade to CoddyKit PRO.
What will I learn in “Monitoring and Debugging Lambda Functions”?
Learn how to observe, log, trace, and troubleshoot AWS Lambda functions in production using CloudWatch, X-Ray, and structured logging. You practise AWS for Backend Developers (EC2, S3, RDS, Lambda) 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 AWS for Backend Developers (EC2, S3, RDS, Lambda)?
No prior experience is required. AWS for Backend Developers (EC2, S3, RDS, Lambda) 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 “Monitoring and Debugging Lambda Functions” 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 AWS for Backend Developers (EC2, S3, RDS, Lambda) lesson?
Yes. Every AWS for Backend Developers (EC2, S3, RDS, Lambda) 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
- What is AWS Lambda?
- Building Your First Lambda Function
- Lambda Triggers and Integrations
- Monitoring and Debugging Lambda Functions