Tratamento de erros e novas tentativas
Implemente mecanismos robustos de tratamento de erros, configure novas tentativas automáticas e compreenda os erros de invocação para criar sistemas sem servidor mais resilientes.
Tratamento de erros e novas tentativas é uma aula grátis de Serverless AWS Lambda Development 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 AWS Lambda Development, e seu progresso é sincronizado entre a web e o app CoddyKit. O curso de Serverless AWS Lambda Development inclui 4 aulas no total.
Partes desta aula ainda não foram traduzidas e aparecem em inglês.
Why Error Handling Matters
In serverless applications, things can go wrong. Your function might fail, a dependency might be unavailable, or an event might be malformed.
Robust error handling is crucial for building resilient systems that can recover gracefully and notify you when issues occur. This lesson explores how AWS Lambda helps you achieve this.
Types of Lambda Errors
When working with Lambda, it's helpful to understand different types of errors:
- Invocation Errors: Problems occurring before your code runs, like incorrect IAM permissions for Lambda to read from an event source.
- Function Errors: Exceptions thrown by your function code, timeouts, or out-of-memory errors. These are the errors you primarily handle within your code.
- Service Errors: Rare issues with the underlying AWS Lambda service itself.
Sync vs. Async Error Paths
How Lambda handles errors depends on the invocation type:
- Synchronous: (e.g., via API Gateway, ALB) Lambda returns the error directly to the caller. The caller is responsible for retries.
- Asynchronous: (e.g., via S3, SNS, SQS) Lambda places the event in an internal queue and automatically retries the function if it fails. You don't get immediate feedback.
We'll focus mostly on asynchronous error handling and retries in this lesson.
Lambda's Async Retries
For asynchronous invocations, Lambda automatically retries your function if it fails due to an unhandled exception or times out.
- By default, Lambda retries twice (total of 3 attempts).
- These retries are automatic and happen with a delay, often with exponential backoff.
- This built-in mechanism helps ensure temporary issues don't lead to lost events.
Configuring Async Retries
You can customize the asynchronous invocation settings for your Lambda function:
- Maximum retry attempts: Set this from 0 to 2. Setting it to 0 means no retries.
- Maximum event age: Define how long Lambda should keep an event in its queue for retries, from 60 seconds to 6 hours.
These settings give you control over how long and how often Lambda attempts to process a failed event.
Catching Failed Events with DLQs
Even with retries, some events might still fail consistently (e.g., due to malformed data). These are often called 'poison pill' messages.
A Dead Letter Queue (DLQ) is a designated destination (an SQS queue or SNS topic) where Lambda sends events that have exhausted all retry attempts.
DLQs are vital for debugging, preventing data loss, and analyzing why certain events couldn't be processed.
Setting Up Your DLQ
To use a DLQ:
- Create an Amazon SQS queue or SNS topic.
- Configure your Lambda function's asynchronous invocation settings to point to this SQS queue or SNS topic as its DLQ.
- Ensure your Lambda function's execution role has permissions to send messages to the chosen DLQ (e.g.,
sqs:SendMessageorsns:Publish).
This ensures that no event is truly 'lost' even after multiple failures.
Handling Errors in Your Code
While Lambda handles retries, you should still implement error handling within your function code using try-catch blocks. This allows you to:
- Gracefully manage expected errors.
- Log detailed context for debugging.
- Perform cleanup or partial rollbacks before re-throwing an exception to trigger Lambda's retry mechanism.
Try running this simple Java example:
public class Main {
public static void main(String[] args) {
processData("valid data");
System.out.println("------------------");
processData("data with error");
}
public static void processData(String data) {
try {
System.out.println("Attempting to process: " + data);
if (data.contains("error")) {
throw new RuntimeException("Critical processing error!");
}
System.out.println("Successfully processed: " + data.toUpperCase());
} catch (Exception e) {
System.err.println("Caught an error: " + e.getMessage());
System.err.println("Further action (e.g., logging, retry logic) would go here.");
// In a real Lambda, re-throwing would trigger a retry for async invocations
}
}
}Understanding Invocation Errors
Sometimes, Lambda can't even start your function. These are invocation errors.
- Examples: Incorrect IAM permissions for Lambda to access an S3 bucket trigger, a misconfigured VPC, or exceeding service quotas before execution.
- Detection: These errors often appear in CloudWatch Logs for your function or as `Invocation errors` metrics in the Lambda console. They are not typically handled by your function's
try-catchblocks.
Quick Check on Retries
Let's test your understanding of error handling and retries in AWS Lambda.
Recap: Building Resilient Lambdas
You've learned how to make your serverless applications more robust:
- Differentiated between various types of Lambda errors.
- Understood how synchronous vs. asynchronous invocations handle errors differently.
- Explored Lambda's automatic retry mechanism for asynchronous calls.
- Discovered the importance of Dead Letter Queues (DLQs) for failed events.
- Saw how to implement basic error handling within your code using
try-catch.
By applying these techniques, you can build more resilient and 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 AWS Lambda Development, atualize para CoddyKit PRO. O curso de Serverless AWS Lambda Development inclui 4 aulas no total.
O que vou aprender em “Tratamento de erros e novas tentativas”?
Implemente mecanismos robustos de tratamento de erros, configure novas tentativas automáticas e compreenda os erros de invocação para criar sistemas sem servidor mais resilientes. Você pratica Serverless AWS Lambda Development 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 AWS Lambda Development?
Nenhuma experiência prévia é necessária. Serverless AWS Lambda Development 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 “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 AWS Lambda Development?
Sim. Cada aula de Serverless AWS Lambda Development 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
- Registros e métricas do CloudWatch
- Tratamento de erros e novas tentativas
- Depuração de aplicativos sem servidor
- Métricas Personalizadas e Alarmes do CloudWatch