비동기 Lambda 호출
비동기 Lambda 호출의 세부 사항을 익히고 이벤트 소스, 재시도, 장시간 실행 작업이나 일괄 처리에 대한 이점을 이해합니다.
비동기 Lambda 호출은(는) CoddyKit의 무료 Serverless AWS Lambda Development 강의입니다. 이것은 4개 중 1번째 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.
What is Asynchronous Invocation?
Welcome! In serverless, functions can be invoked in different ways. An asynchronous invocation means the caller doesn't wait for the function to finish executing.
Think of it like sending a letter: you drop it in the mailbox, and you don't wait for the recipient to read it. You trust it will be delivered and processed later.
Sync vs. Async: The Key Difference
When you invoke a Lambda function synchronously, you wait for a response immediately. Your application pauses until Lambda returns a result or an error.
With asynchronous invocation, Lambda places the event in an internal queue and immediately returns a success message to the caller. The actual function execution happens in the background.
How Asynchronous Invocation Works
When an event triggers an asynchronous Lambda invocation:
- Lambda receives the event from the caller (e.g., S3, SNS).
- It places the event in an internal queue.
- Lambda sends an immediate success response to the caller.
- Later, Lambda retrieves the event from the queue and invokes your function.
- The function processes the event, and any output is discarded.
Invocation Types in Practice
When you invoke a Lambda function directly via the AWS SDK or CLI, you specify an InvocationType parameter:
RequestResponse: For synchronous invocations (you wait for a response).Event: For asynchronous invocations (fire-and-forget).DryRun: To validate parameters without invoking.
Many AWS services (like S3, SNS, EventBridge) inherently invoke Lambda asynchronously when configured as triggers.
Benefits: Decoupling and Scalability
Asynchronous invocations offer significant advantages:
- Decoupling: The caller doesn't depend on the function's immediate response. It can continue its work without waiting.
- Scalability: Lambda can buffer events in its internal queue during traffic spikes, preventing your function from being overwhelmed and ensuring events are eventually processed.
- Resilience: If your function fails, Lambda can automatically retry the invocation.
Ideal for Long-Running Tasks
Asynchronous invocation is perfect for tasks that might take a while to complete, like:
- Processing large files uploaded to S3.
- Sending email notifications.
- Transcoding videos.
- Updating multiple databases.
The client doesn't need to wait for these operations, improving user experience and application responsiveness.
Asynchronous Retries Explained
By default, if an asynchronously invoked Lambda function fails, Lambda automatically retries the invocation twice, with an exponential backoff between attempts.
This built-in retry mechanism enhances the reliability of your serverless applications by handling transient errors without manual intervention.
Configuring Retry Behavior
You can customize the retry behavior for asynchronous invocations:
- Maximum event age: How long Lambda should keep an event in the queue before discarding it (default: 6 hours).
- Maximum retry attempts: How many times Lambda should retry the function (0 to 2 attempts).
These settings help control how long your system tries to process a failed event.
Example: Processing an Uploaded Image
Imagine a user uploads an image to an S3 bucket. You want to resize it and add a watermark.
You can configure the S3 bucket to trigger a Lambda function whenever a new image is uploaded. S3 will asynchronously invoke your Lambda, which then processes the image. The user doesn't wait for the resizing to complete.
Lambda Function for Async Processing
Here's a simple Python Lambda function that could be invoked asynchronously. It simulates a long-running task.
When invoked asynchronously, the caller won't wait for the time.sleep() to finish.
import json
import time
def lambda_handler(event, context):
print("Received event:", json.dumps(event, indent=2))
# Simulate a long-running task
print("Starting long-running task...")
time.sleep(5) # Pause for 5 seconds
print("Task completed!")
# For async invocations, the return value is usually ignored
return {
'statusCode': 200,
'body': json.dumps('Processing complete!')
}Quick Check on Async
You've learned about the core concepts of asynchronous Lambda invocations.
Which of the following is a primary benefit of using asynchronous Lambda invocations?
Recap: Asynchronous Power
Great job! You've mastered the basics of asynchronous Lambda invocations.
- They allow callers to "fire-and-forget" events.
- Lambda uses an internal queue for processing.
- Benefits include decoupling, scalability, and handling long-running tasks.
- Built-in retry mechanisms enhance reliability.
This pattern is fundamental for building robust and scalable event-driven serverless applications. Next, we'll look at handling failures effectively with Dead Letter Queues!
자주 묻는 질문
“비동기 Lambda 호출” 강의는 무료인가요?
네 — “비동기 Lambda 호출” 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.
“비동기 Lambda 호출”에서 뭘 배우나요?
비동기 Lambda 호출의 세부 사항을 익히고 이벤트 소스, 재시도, 장시간 실행 작업이나 일괄 처리에 대한 이점을 이해합니다. 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 1번째 강의입니다.
“비동기 Lambda 호출” 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.