오류 처리 및 재시도
견고한 오류 처리 메커니즘을 구현하고 자동 재시도를 구성하며 호출 오류를 이해하여 더욱 탄력적인 서버리스 시스템을 구축합니다.
오류 처리 및 재시도은(는) CoddyKit의 무료 Serverless AWS Lambda Development 강의입니다. 이것은 4개 중 2번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 Serverless AWS Lambda Development 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. Serverless AWS Lambda Development 강의에는 총 4개의 강의가 포함되어 있습니다.
이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.
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.
자주 묻는 질문
“오류 처리 및 재시도” 강의는 무료인가요?
네 — “오류 처리 및 재시도” 전체 내용을 이 웹사이트에서 무료로 읽을 수 있습니다. 인터랙티브하게 실습하려면(내장 코드 에디터와 24/7 AI 튜터), CoddyKit PRO로 업그레이드하면 Serverless AWS Lambda Development 강의 전체를 잠금 해제할 수 있습니다. Serverless AWS Lambda Development 강의에는 총 4개의 강의가 포함되어 있습니다.
“오류 처리 및 재시도”에서 뭘 배우나요?
견고한 오류 처리 메커니즘을 구현하고 자동 재시도를 구성하며 호출 오류를 이해하여 더욱 탄력적인 서버리스 시스템을 구축합니다. 브라우저에서 직접 실행하는 실습 코드로 Serverless AWS Lambda Development을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.
Serverless AWS Lambda Development을(를) 시작하는 데 경험이 필요한가요?
사전 경험은 필요하지 않습니다. CoddyKit의 Serverless AWS Lambda Development은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 2번째 강의입니다.
“오류 처리 및 재시도” 강의는 얼마나 걸리나요?
대부분의 CoddyKit 강의는 약 5~10분이 소요됩니다. 각 강의는 간결하고 인터랙티브하여 꾸준한 진행이 가능하며, 웹과 앱에서 중단한 부분부터 바로 시작할 수 있습니다.
이 Serverless AWS Lambda Development 강의에서 코드를 작성하고 실행할 수 있나요?
네. 모든 Serverless AWS Lambda Development 강의에는 내장 코드 에디터가 포함되어 있으므로, 브라우저에서 바로 실제 코드를 작성하고 실행한 후 즉시 AI 피드백을 받을 수 있습니다 — 로컬 설정이 필요 없습니다.