Guided Lab: Custom Error Handling with AWS Lambda

Tutorials-Dojo

Description

AWS Lambda is a serverless computing service that lets you run code without provisioning or managing servers. It automatically scales your applications by running code in response to events such as data changes, system state shifts, or user actions. One common use case for Lambda functions is handling errors gracefully in your applications or integrations with AWS services.

In this lab, you will create a custom error-handling Lambda function that simulates error scenarios and outputs meaningful error messages for debugging and monitoring.

Prerequisites

This lab assumes you have the following:

Basic knowledge and understanding of AWS Lambda
Python Programming

If you find any gaps in your knowledge, consider taking the following lab:

Creating an AWS Lambda function

Objectives

By the end of this lab, you will:

Simulate custom errors and learn how to handle them effectively.
Understand the basics of error logging using Amazon CloudWatch.

Subscribe to access AWS PlayCloud Labs

Lab Steps

Creating the AWS Lambda Function

1. Navigate to AWS Lambda Console

2. Create Function using the following confgurations:

Choose Author from scratch.
Function name: CustomErrorHandler
Select Python 3.12 as the runtime.
Execution role:
- Select Use an Existing Role: PlayCloud-Sanbox
Click on Create Function

Write the Custom Error Handling Code

1. Scroll down to the Code source section.

2. Replace the default code with the following Python code:

Note: We are using the old console editor for this lab. You’re welcome to use either the old or new editor, whichever you prefer; the steps remain the same, though the interface may have a slightly different appearance in the new editor.

import logging
import json

# Set up logging
logger = logging.getLogger()
logger.setLevel(logging.INFO)

# Custom exception class
class CustomError(Exception):
    def __init__(self, message):
        self.message = message
        super().__init__(self.message)

def lambda_handler(event, context):
    try:
        # Simulating an error scenario
        if 'trigger_error' in event and event['trigger_error']:
            raise CustomError("This is a custom error message for simulation purposes.")
        
        # Normal processing logic
        return {
            'statusCode': 200,
            'body': json.dumps('Function executed successfully!')
        }
    except CustomError as e:
        logger.error(f"Custom error occurred: {e.message}")
        return {
            'statusCode': 400,
            'body': json.dumps(f"Error: {e.message}")
        }
    except Exception as e:
        logger.error(f"An unexpected error occurred: {str(e)}")
        return {
            'statusCode': 500,
            'body': json.dumps(f"Internal Server Error: {str(e)}")
        }

Test the Lambda Function

1. Click on Test to create a new test event.

2. Name your test event TestEvent.

3. Use the following sample event to simulate a normal execution:

{
    "trigger_error": false
}

4. Save. Then, click Test again. The function should return a successful response: "Function executed successfully!".

5. Now, simulate an error scenario:

Modify the test event to trigger the custom error:

{
    "trigger_error": true
}

5. Save it. Click Test. This time, the function should return an error message: "Error: This is a custom error message for simulation purposes."

View Logs in Amazon CloudWatch

1. Click on the Monitoring tab.

2. Select View logs in CloudWatch.

3. In CloudWatch Logs, find the latest log stream for your function.

4. Review the logs to see the messages printed by your function.

Congratulations! You should now know and understand how to implement custom error handling in AWS Lambda. Proper error handling is essential for building resilient and maintainable serverless applications. By simulating errors and logging them in Amazon CloudWatch, you can monitor, debug, and improve the reliability of your Lambda-based solutions.

As a best practice, remember to delete any resources no longer in use, such as Lambda functions, to maintain a clutter-free AWS environment.

Thank you for joining this lab, and happy learning!