Variáveis de ambiente e camadas
Gerencie configurações e dependências com eficiência usando variáveis de ambiente e camadas do Lambda para compartilhar código.
Variáveis de ambiente e camadas é uma aula grátis de Serverless Backend with AWS Lambda & API Gateway no CoddyKit. Esta é a aula 2 de 4. Você pode ler a aula completa abaixo gratuitamente — depois pratica ao vivo no navegador com um editor de código integrado e um tutor de IA 24/7. Faz parte do caminho de aprendizado de Serverless Backend with AWS Lambda & API Gateway, e seu progresso é sincronizado entre a web e o app CoddyKit. O curso de Serverless Backend with AWS Lambda & API Gateway inclui 4 aulas no total.
Partes desta aula ainda não foram traduzidas e aparecem em inglês.
Configuring Lambda Functions
When building serverless applications, you often need to configure your Lambda functions. This includes settings that change between development, testing, and production environments.
Think about database connection strings, API endpoints, or feature flags. Hardcoding these values is a bad practice!
What are Environment Variables?
Environment variables are key-value pairs that you define for your Lambda function. Your function's code can then access these variables at runtime.
- They provide a simple way to change your function's behavior without modifying its code.
- Each function has its own set of environment variables.
Setting Environment Variables
You can set environment variables directly in the AWS Management Console when configuring your Lambda function. They can also be defined using Infrastructure as Code tools like AWS SAM or CloudFormation.
Important: While convenient, avoid storing sensitive information like database passwords directly in environment variables. Use AWS Secrets Manager for that!
Accessing Env Vars in Python
In Python, you can access environment variables using the os module, specifically os.environ.get(). This method allows you to provide a default value if the variable isn't set.
Try running this example:
import os
def lambda_handler(event, context):
# Get GREETING_MESSAGE env var, default to 'Hello'
greeting = os.environ.get('GREETING_MESSAGE', 'Hello')
# Get 'name' from the event, default to 'World'
name = event.get('name', 'World')
message = f"{greeting}, {name}!"
print(message)
return {
'statusCode': 200,
'body': message
}
# --- Local testing simulation ---
if __name__ == '__main__':
# Simulate setting an environment variable locally
os.environ['GREETING_MESSAGE'] = 'Hola'
# Simulate a Lambda event
test_event = {'name': 'CoddyKit User'}
print("\nRunning lambda_handler locally...")
result = lambda_handler(test_event, None)
print(f"Local Lambda response: {result}")
# Clean up simulated env var
del os.environ['GREETING_MESSAGE']
Env Var Best Practices
Using environment variables wisely can greatly improve your function's maintainability:
- Non-sensitive config: Use for API keys (for non-critical services), log levels, feature flags.
- Integration with Secrets Manager: For truly sensitive data (e.g., database credentials), store them in AWS Secrets Manager and retrieve them at runtime using your function's IAM role.
- Separate environments: Easily switch configs for dev, staging, and production.
Introducing Lambda Layers
As your serverless applications grow, you might find multiple Lambda functions needing the same libraries, dependencies, or utility code.
Lambda Layers solve this by allowing you to package and share common components across multiple functions.
Benefits of Lambda Layers
Layers offer several advantages for managing your Lambda functions:
- Smaller deployment packages: Your function code only contains your business logic, not large libraries.
- Code reusability: Share common functions, helper modules, or SDKs across many Lambdas.
- Faster deployments: Only upload your small function code, not entire dependency sets.
- Consistent dependencies: Ensure all functions use the same version of a library.
How Lambda Layers Work
When you attach a layer to a Lambda function, AWS extracts its contents into the /opt directory in the function's execution environment.
Your function code can then import modules or use binaries from this /opt directory as if they were part of its own deployment package.
Using a Shared Layer (Python)
Once a layer is attached, your Python function can simply import modules from it. For example, if your layer contains my_utilities.py at python/my_utilities.py, you can import it like any other module:
from my_utilities import format_message
import json
def lambda_handler(event, context):
user_name = event.get('name', 'Guest')
# Assuming format_message is in our layer
response_message = format_message(user_name)
return {
'statusCode': 200,
'body': json.dumps({'message': response_message})
}
This code isn't runnable on its own as the layer isn't defined here, but it shows how you'd import from it.
from my_utilities import format_message
import json
def lambda_handler(event, context):
user_name = event.get('name', 'Guest')
# Assuming format_message is in our layer
response_message = format_message(user_name)
return {
'statusCode': 200,
'body': json.dumps({'message': response_message})
}
Quick Check: Env Vars & Layers
Let's test your understanding of Lambda environment variables and layers.
Recap: Env Vars & Layers
In this lesson, we learned how to manage Lambda function configurations and dependencies effectively:
- Environment Variables: Key-value pairs for non-sensitive configuration, accessed via
os.environin Python. - Lambda Layers: Mechanisms for packaging and sharing common code, libraries, and dependencies across multiple functions.
- Layers lead to smaller deployment packages, improved reusability, and faster deployments.
Next up: Dive into logging and monitoring your Lambda functions with CloudWatch!
Perguntas Frequentes
A aula “Variáveis de ambiente e camadas” é grátis?
Sim — o texto completo de “Variáveis de ambiente e camadas” é grátis para ler aqui na web. Para praticá-la interativamente (um editor de código integrado e um tutor de IA 24/7) e desbloquear o restante do curso de Serverless Backend with AWS Lambda & API Gateway, atualize para CoddyKit PRO. O curso de Serverless Backend with AWS Lambda & API Gateway inclui 4 aulas no total.
O que vou aprender em “Variáveis de ambiente e camadas”?
Gerencie configurações e dependências com eficiência usando variáveis de ambiente e camadas do Lambda para compartilhar código. Você pratica Serverless Backend with AWS Lambda & API Gateway com código prático que executa diretamente no navegador, e um tutor de IA 24/7 responde suas dúvidas enquanto trabalha na aula.
Preciso ter experiência prévia para começar Serverless Backend with AWS Lambda & API Gateway?
Nenhuma experiência prévia é necessária. Serverless Backend with AWS Lambda & API Gateway no CoddyKit é estruturado para alunos iniciantes até avançados, então você pode começar aqui ou desde o início e aprender no seu ritmo. Esta é a aula 2 de 4.
Quanto tempo leva a aula “Variáveis de ambiente e camadas”?
A maioria das aulas CoddyKit leva cerca de 5–10 minutos. Cada uma é compacta e interativa, então você faz progresso constante e retoma exatamente de onde parou entre web e app.
Posso escrever e executar código nesta aula de Serverless Backend with AWS Lambda & API Gateway?
Sim. Cada aula de Serverless Backend with AWS Lambda & API Gateway inclui um editor de código integrado, então você escreve e executa código real direto no navegador e recebe feedback de IA instantaneamente — nenhuma configuração local necessária.
Todas as aulas deste curso
- Ambiente de execução e manipulador do Lambda
- Variáveis de ambiente e camadas
- Registro e monitoramento com o CloudWatch
- Tratamento de erros, repetições e filas de mensagens não entregues