Tratamento de erros e novas tentativas
Implemente um tratamento robusto de erros, filas de mensagens não entregues e mecanismos de novas tentativas para aplicações sem servidor resilientes.
Tratamento de erros e novas tentativas é uma aula grátis de Serverless Backend with AWS Lambda & API Gateway no CoddyKit. Esta é a aula 3 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.
Build Resilient Serverless Apps
In serverless architectures, things can go wrong. Network issues, service outages, or bugs in your code can all lead to failures.
Building resilient applications means they can recover gracefully from these issues, minimizing impact on users and preventing data loss. Error handling and retries are key to this.
Lambda Invocation Types
How Lambda handles errors and retries depends on how your function is invoked. There are two main types:
- Synchronous: The caller waits for a response (e.g., API Gateway, ALB).
- Asynchronous: The caller doesn't wait; Lambda queues the event (e.g., S3, SNS, SQS, EventBridge).
Each type has different retry behaviors by default.
Synchronous Invocation Retries
When a Lambda function is invoked synchronously and returns an error (or times out), Lambda does NOT automatically retry the function.
It's up to the service or client that invoked Lambda (e.g., API Gateway, your mobile app) to implement its own retry logic. Lambda simply passes the error back to the caller.
Asynchronous Invocation Retries
For asynchronous invocations, Lambda has built-in retry mechanisms. If your function fails due to an unhandled error or times out, Lambda will automatically retry the invocation twice.
This means a total of three attempts (initial + two retries) are made, with an exponential backoff between retries. This helps overcome transient issues.
Handling Errors in Code
Beyond Lambda's automatic retries, you should always implement error handling *within* your function code. This allows you to:
- Gracefully manage expected errors (e.g., missing input).
- Log specific details for debugging.
- Return custom error messages to callers.
In Python, the try-except block is your best friend for this.
Python Error Handling Example
This Python Lambda function uses try-except to handle potential KeyError if an expected key is missing, or ZeroDivisionError if a value is zero. Try running it with different inputs!
import json
def lambda_handler(event, context):
try:
# Expecting 'value' key in the event
num = event['value']
result = 100 / num
return {
'statusCode': 200,
'body': json.dumps(f'Result: {result}')
}
except KeyError:
print("Error: 'value' key missing in event.")
return {
'statusCode': 400,
'body': json.dumps('Input Error: Missing \'value\' in event.')
}
except ZeroDivisionError:
print("Error: Cannot divide by zero.")
return {
'statusCode': 400,
'body': json.dumps('Input Error: Cannot divide by zero.')
}
except Exception as e:
print(f"An unexpected error occurred: {e}")
return {
'statusCode': 500,
'body': json.dumps(f'Server Error: {str(e)}')
}
# Example of how to run locally for testing
if __name__ == "__main__":
# Test case 1: Missing key
print("\n--- Test Case 1 (Missing Key) ---")
print(lambda_handler({}, None))
# Test case 2: Zero division
print("\n--- Test Case 2 (Zero Division) ---")
print(lambda_handler({'value': 0}, None))
# Test case 3: Success
print("\n--- Test Case 3 (Success) ---")
print(lambda_handler({'value': 25}, None))
# Test case 4: Non-numeric value (unhandled, falls to generic exception)
print("\n--- Test Case 4 (Type Error) ---")
print(lambda_handler({'value': 'abc'}, None))Dead-Letter Queues (DLQs)
What happens if an asynchronous Lambda invocation fails even after all retries? This is where Dead-Letter Queues (DLQs) come in!
A DLQ is an Amazon SQS queue or SNS topic where Lambda sends events it couldn't process successfully after all retry attempts. It's a crucial mechanism for:
- Preventing data loss.
- Debugging persistent issues.
- Manual reprocessing of failed events.
Configuring a DLQ
To set up a DLQ for your Lambda function:
- Create an SQS queue or SNS topic: This will be your DLQ.
- Grant Permissions: Ensure your Lambda function has permission to publish messages to the chosen SQS queue or SNS topic.
- Configure Lambda: In your Lambda function's configuration (under 'Asynchronous invocation'), specify the ARN of your SQS queue or SNS topic as the DLQ.
This ensures failed events have a safe landing spot.
DLQ Behavior in Action
It's important to understand *when* an event is sent to a DLQ:
- Only for asynchronous invocations.
- After all automatic retry attempts (initial + two retries) have failed.
- If the event's maximum age is exceeded, or the maximum retry attempts are exhausted.
The original event payload, along with some metadata, is sent to the DLQ.
DLQ Understanding
Let's check your understanding of Dead-Letter Queues!
Recap: Error Handling & Retries
You've learned how to make your serverless applications more robust!
- Synchronous vs. Asynchronous: Different invocation types have different default retry behaviors.
- In-code Error Handling: Use
try-exceptto catch and manage errors within your Lambda code. - Dead-Letter Queues (DLQs): A critical mechanism for capturing and inspecting events that fail after all automatic retries, preventing data loss for async invocations.
These practices are essential for building reliable serverless systems!
Perguntas Frequentes
A aula “Tratamento de erros e novas tentativas” é grátis?
Sim — o texto completo de “Tratamento de erros e novas tentativas” 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 “Tratamento de erros e novas tentativas”?
Implemente um tratamento robusto de erros, filas de mensagens não entregues e mecanismos de novas tentativas para aplicações sem servidor resilientes. 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 3 de 4.
Quanto tempo leva a aula “Tratamento de erros e novas tentativas”?
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
- Inicializações a frio e estratégias de aquecimento
- Técnicas de otimização de custos
- Tratamento de erros e novas tentativas
- Observabilidade com registros estruturados e rastreamento