AWS for Backend Developers (EC2, S3, RDS, Lambda) · Lesson

Lambda Layers and Environment Variables

Streamline code deployment and management using Lambda Layers for dependencies and environment variables for configuration.

Lambda Layers and Environment Variables is a free AWS for Backend Developers (EC2, S3, RDS, Lambda) lesson on CoddyKit — lesson 2 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.

What are Lambda Layers?

AWS Lambda Layers help you manage common dependencies and custom runtimes more efficiently. Think of them as shared libraries for your functions.

Instead of bundling all your code and dependencies with every function deployment, you can package reusable components into a Layer.

Why Use Lambda Layers?

Layers offer several benefits for your serverless applications:

Smaller Deployment Packages: Keep your function code lean by separating dependencies.
Code Reusability: Share common code (e.g., utility functions, database connectors) across multiple Lambda functions.
Faster Deployments: Smaller packages upload quicker.
Easier Updates: Update a dependency once in a layer, and all functions using it benefit.

How Layers are Structured

A Lambda Layer is essentially a .zip file archive containing library code, custom runtimes, or other dependencies.

When you attach a layer to a function, Lambda extracts its content to the /opt directory in the function's execution environment. Your function code can then import modules from /opt.

Imagining a Simple Layer

Let's say you have a common logging utility or a specific SDK version you want to use. Instead of including it in every Lambda function's deployment package, you'd put it in a layer.

The layer's ZIP file structure might look like this for Python:

python/mylogger.py

Your Lambda function would then simply import it as import mylogger.

Attaching a Layer to Lambda

You can attach up to 5 layers to a single Lambda function. This is typically done through the AWS Management Console, AWS CLI, or Infrastructure as Code tools like SAM or CloudFormation.

When attaching, you specify the Layer ARN (Amazon Resource Name) which uniquely identifies the layer and its specific version.

Layer Demo: Shared Utility

Imagine we have a layer containing a utils.py with a greet function. Here's how a Lambda function would use it. (We simulate the layer's presence for this runnable demo):

import json

# In a real Lambda, 'utils' would be imported
# from a layer mounted at /opt/python/utils.py
# For this demo, we simulate the 'utils' module.
class Utils:
    @staticmethod
    def greet(name):
        return f"Hello, {name} from Layer!"
utils = Utils() # Make it available as 'utils'

def lambda_handler(event, context):
    name = event.get('name', 'World')
    message = utils.greet(name)
    
    return {
        'statusCode': 200,
        'body': json.dumps(message)
    }

if __name__ == "__main__":
    # Simulate a test event
    test_event = {'name': 'Coddy'}
    result = lambda_handler(test_event, None)
    print(result['body'])
    
    test_event_default = {}
    result_default = lambda_handler(test_event_default, None)
    print(result_default['body'])

What are Env Variables?

Environment variables allow you to pass configuration settings to your Lambda function without changing its underlying code.

They are key-value pairs that are available to your function's code at runtime. This is ideal for settings that vary between environments (e.g., development, test, production) or for non-sensitive configuration data.

Setting Env Variables in Lambda

You can define environment variables when you create or update your Lambda function. This is typically done via:

AWS Management Console: Under the function's "Configuration" tab, then "Environment variables".
AWS CLI: Using the --environment "Variables={KEY=VALUE}" parameter.
Infrastructure as Code: For example, in a SAM template, under the function's Environment: Variables: section.

Important: For highly sensitive data like database passwords or API keys, always use AWS Secrets Manager instead of environment variables.

Env Variables Demo: Config

Let's say you have an environment variable named GREETING_PREFIX set to "Welcome". Your Lambda function can easily access its value using the os module in Python:

import os
import json

def lambda_handler(event, context):
    # Access environment variables
    # os.environ.get('KEY', 'default_value')
    prefix = os.environ.get('GREETING_PREFIX', 'Hello')
    name = event.get('name', 'User')
    
    message = f"{prefix}, {name}!"
    
    return {
        'statusCode': 200,
        'body': json.dumps(message)
    }

if __name__ == "__main__":
    # Simulate setting an environment variable locally
    os.environ['GREETING_PREFIX'] = 'Hola'
    
    test_event = {'name': 'Amigo'}
    result = lambda_handler(test_event, None)
    print(result['body'])
    
    # Clean up and test default behavior
    del os.environ['GREETING_PREFIX'] 
    test_event_default = {'name': 'World'}
    result_default = lambda_handler(test_event_default, None)
    print(result_default['body'])

Check Your Knowledge

Which of the following are valid reasons to use AWS Lambda Layers?

Recap: Layers & Env Vars

Today, you learned about two powerful tools for managing your Lambda functions more effectively:

Lambda Layers: Used for packaging shared code, libraries, and dependencies, which reduces deployment package size and promotes code reusability across functions.
Environment Variables: Used for passing configuration settings to your function at runtime, making your code more flexible and easier to manage across different deployment environments.

Mastering these features will help you build more organized, efficient, and maintainable serverless applications!

Frequently asked questions

Is the “Lambda Layers and Environment Variables” lesson free?

Yes — the full text of “Lambda Layers and Environment Variables” 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 “Lambda Layers and Environment Variables”?

Streamline code deployment and management using Lambda Layers for dependencies and environment variables for configuration. 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 2 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Lambda Layers and Environment Variables” 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

← Back to AWS for Backend Developers (EC2, S3, RDS, Lambda)