0Pricing
Serverless Backend with AWS Lambda & API Gateway · Lesson

Logging and Monitoring with CloudWatch

Implement robust logging within your Lambda functions and monitor their performance and errors using AWS CloudWatch.

Logging and Monitoring with CloudWatch is a free Serverless Backend with AWS Lambda & API Gateway lesson on CoddyKit — lesson 3 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.

Why Log & Monitor Lambda?

When your Lambda functions run in the cloud, you can't just attach a debugger. This is where logging and monitoring become incredibly important!

They help you understand what your function is doing, debug issues, and ensure it's performing well.

Meet AWS CloudWatch

AWS CloudWatch is the central observability service for AWS. It collects and processes raw data from AWS services (like Lambda) into readable metrics and logs.

  • CloudWatch Logs: Stores your function's text output.
  • CloudWatch Metrics: Gathers performance data (invocations, errors, duration).
  • CloudWatch Alarms: Notifies you when metrics cross defined thresholds.

Lambda Logs Automatically

Good news! AWS Lambda automatically integrates with CloudWatch Logs. Any output your function sends to stdout (standard output) or stderr (standard error) will be captured.

This means simple print() statements in Python, or console.log() in Node.js, will show up in CloudWatch Logs.

Python Logging Module

While print() works, for more robust logging in Python, you should use the built-in logging module. It allows you to:

  • Set different log levels (DEBUG, INFO, WARNING, ERROR, CRITICAL).
  • Include timestamps and other metadata automatically.
  • Format your log messages consistently.

Basic Lambda Logging Demo

Try running this simple Python Lambda function. Notice how both print() and logger.info() messages are captured. In a real Lambda, these would appear in CloudWatch Logs.

import json
import logging

# Configure logging
logger = logging.getLogger()
logger.setLevel(logging.INFO)

def lambda_handler(event, context):
    # Messages from print() go to CloudWatch Logs
    print("Starting Lambda execution!")

    # Messages from the logging module also go to CloudWatch Logs
    logger.info("This is an informational log message.")

    # Log the event received by the Lambda function
    logger.info(f"Received event: {json.dumps(event)}")

    # Simulate some work
    result = "Processing complete."
    logger.info(f"Function result: {result}")

    return {
        'statusCode': 200,
        'body': json.dumps(result)
    }

CloudWatch Log Structure

When Lambda sends logs to CloudWatch, they are organized in a specific way:

  • Log Group: A container for logs from a specific application or service. For Lambda, it's typically /aws/lambda/YOUR_FUNCTION_NAME.
  • Log Stream: Within a Log Group, each instance or invocation of your Lambda function creates a new Log Stream to store its logs.

Viewing Your Lambda Logs

You can access your function's logs in the AWS Console:

  1. Navigate to the Lambda service.
  2. Select your function.
  3. Go to the 'Monitor' tab.
  4. Click 'View logs in CloudWatch' to see the Log Group and Streams.

Here you can filter, search, and analyze your log data to debug issues.

Monitoring Lambda Metrics

Beyond logs, CloudWatch automatically collects metrics for your Lambda functions, giving you insights into their performance and health without any extra code.

Key metrics include:

  • Invocations: Total number of times your function was triggered.
  • Errors: Count of failed invocations.
  • Duration: Execution time of your function.
  • Throttles: When Lambda denied an invocation due to concurrency limits.

Setting Up CloudWatch Alarms

CloudWatch Alarms allow you to set up notifications or actions based on metric thresholds. For example, you can create an alarm that:

  • Triggers if the 'Errors' metric for your function is greater than 0 for 5 minutes.
  • Sends a notification via Amazon SNS (Simple Notification Service) to your email or an alerting system.

This is crucial for proactive monitoring!

CloudWatch Capabilities Check

CloudWatch is a powerful tool for serverless operations. Which of the following are capabilities of AWS CloudWatch when monitoring Lambda functions?

Lesson Summary

Great job! You've learned how critical logging and monitoring are for serverless applications, especially with AWS Lambda.

  • Lambda seamlessly integrates with CloudWatch Logs for capturing output.
  • The Python logging module provides robust logging.
  • CloudWatch Metrics give you insights into function performance.
  • CloudWatch Alarms enable proactive alerts based on these metrics.

These tools are essential for debugging, performance tuning, and maintaining healthy serverless backends.

Frequently asked questions

Is the “Logging and Monitoring with CloudWatch” lesson free?

Yes — the full text of “Logging and Monitoring with CloudWatch” 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 “Logging and Monitoring with CloudWatch”?

Implement robust logging within your Lambda functions and monitor their performance and errors using AWS CloudWatch. 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 3 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Logging and Monitoring with CloudWatch” 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

  1. Lambda Runtime and Handler
  2. Environment Variables and Layers
  3. Logging and Monitoring with CloudWatch
  4. Error Handling, Retries & Dead-Letter Queues
← Back to Serverless Backend with AWS Lambda & API Gateway