AWS for Backend Developers (EC2, S3, RDS, Lambda) · 강의

Lambda 트리거와 통합

Lambda 함수를 S3, DynamoDB 및 API Gateway와 같은 다양한 AWS 서비스에 연결해 강력한 이벤트 기반 작업 흐름을 만듭니다.

레슨 3/411개 단계

Lambda 트리거와 통합은(는) CoddyKit의 무료 AWS for Backend Developers (EC2, S3, RDS, Lambda) 강의입니다. 이것은 4개 중 3번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 AWS for Backend Developers (EC2, S3, RDS, Lambda) 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. AWS for Backend Developers (EC2, S3, RDS, Lambda) 강의에는 총 4개의 강의가 포함되어 있습니다.

이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.

Events Bring Lambda to Life

Welcome to the heart of serverless architecture: Lambda Triggers! These are the events that tell your Lambda function when to run. Instead of constantly running a server, your function springs into action only when needed.

Think of it like a doorbell for your code. Someone presses the button (an event occurs), and your function responds.

How Triggers Work: Push vs. Pull

Lambda triggers come in two main flavors:

Push-based: The event source (like S3 or SNS) directly invokes your Lambda function when an event happens. Lambda receives the event and runs your code.
Pull-based: Lambda itself polls an event source (like SQS queues or DynamoDB Streams) for new items. When new data is found, Lambda retrieves it and invokes your function.

Understanding this helps you design efficient event-driven workflows.

S3 Event Triggers: React to Storage

One of the most common and powerful triggers is Amazon S3. You can configure an S3 bucket to automatically invoke a Lambda function whenever specific events occur, such as:

New object created (e.g., an image upload)
Object deleted
Object restored

This is perfect for tasks like image resizing, data validation, or generating thumbnails as soon as a file is uploaded.

S3 Trigger Demo: Logging Uploads

Here's a basic Python Lambda function that would be triggered by an S3 object creation event. It simply logs the bucket and object key from the event data.

Try running the simulated event:

import json

def lambda_handler(event, context):
    """
    Simulated Lambda handler for S3 events.
    Logs the details of the S3 event.
    """
    print("--- S3 Event Received ---")
    for record in event.get('Records', []):
        bucket_name = record['s3']['bucket']['name']
        object_key = record['s3']['object']['key']
        event_name = record['eventName']
        print(f"Bucket: {bucket_name}")
        print(f"Object: {object_key}")
        print(f"Event: {event_name}")
    print("-------------------------")
    return {
        'statusCode': 200,
        'body': json.dumps('S3 event logged!')
    }

if __name__ == "__main__":
    # Simulate an S3 PUT event
    mock_event = {
        "Records": [
            {
                "eventSource": "aws:s3",
                "eventName": "ObjectCreated:Put",
                "s3": {
                    "bucket": {"name": "my-cool-bucket"},
                    "object": {"key": "my-new-file.txt"}
                }
            }
        ]
    }
    lambda_handler(mock_event, None)

DynamoDB Streams: Database Changes

Amazon DynamoDB Streams provide a time-ordered sequence of item-level modifications in a DynamoDB table. When you enable a stream, every create, update, or delete operation is captured.

Lambda can be configured to read from these streams, allowing you to react to database changes in real-time. Use cases include:

Data replication across tables
Auditing changes
Triggering downstream workflows

DynamoDB Stream Demo: Processing Updates

This Python Lambda function simulates processing events from a DynamoDB Stream. It logs the event type (INSERT, MODIFY, REMOVE) and the keys/new image of the affected item.

Run it to see how a database change event looks:

import json

def lambda_handler(event, context):
    """
    Simulated Lambda handler for DynamoDB Stream events.
    Logs the details of the changed records.
    """
    print("--- DynamoDB Stream Event Received ---")
    for record in event.get('Records', []):
        event_name = record['eventName']
        keys = record['dynamodb']['Keys']
        new_image = record['dynamodb'].get('NewImage', {})
        print(f"Event: {event_name}")
        print(f"Keys: {json.dumps(keys)}")
        print(f"New Image: {json.dumps(new_image)}")
    print("------------------------------------")
    return {
        'statusCode': 200,
        'body': json.dumps('DynamoDB stream processed!')
    }

if __name__ == "__main__":
    # Simulate a DynamoDB INSERT event
    mock_event = {
        "Records": [
            {
                "eventID": "1",
                "eventName": "INSERT",
                "dynamodb": {
                    "Keys": {"id": {"S": "123"}},
                    "NewImage": {"id": {"S": "123"}, "name": {"S": "Alice"}},
                    "StreamViewType": "NEW_AND_OLD_IMAGES"
                }
            }
        ]
    }
    lambda_handler(mock_event, None)

API Gateway: Serverless API Endpoints

Amazon API Gateway acts as a 'front door' for applications to access backend services, including Lambda functions. It handles all the tasks involved in accepting and processing up to hundreds of thousands of concurrent API calls.

By integrating API Gateway with Lambda, you can build powerful, scalable, and secure RESTful APIs without managing any servers. Users make an HTTP request, API Gateway routes it to your Lambda, and your Lambda returns a response.

API Gateway Demo: Your Serverless API

This Lambda function shows how to respond to an API Gateway request. It receives event data about the HTTP request and returns a JSON response, which API Gateway then sends back to the client.

Run the simulation to see the expected output:

import json

def lambda_handler(event, context):
    """
    Simulated Lambda handler for API Gateway events.
    Returns a simple JSON response.
    """
    print("--- API Gateway Event Received ---")
    print(f"HTTP Method: {event.get('httpMethod')}")
    print(f"Path: {event.get('path')}")
    print("----------------------------------")

    response_body = {
        "message": "Hello from your serverless API!",
        "input": event
    }
    return {
        'statusCode': 200,
        'headers': {
            'Content-Type': 'application/json'
        },
        'body': json.dumps(response_body)
    }

if __name__ == "__main__":
    # Simulate an API Gateway GET request event
    mock_event = {
        "resource": "/",
        "path": "/",
        "httpMethod": "GET",
        "headers": {
            "Accept": "text/html"
        },
        "queryStringParameters": None,
        "pathParameters": None,
        "body": None,
        "isBase64Encoded": False
    }
    response = lambda_handler(mock_event, None)
    print("\n--- API Response ---")
    print(json.dumps(response, indent=2))

More Powerful Integrations

Lambda can integrate with many other AWS services to build incredibly flexible architectures:

Amazon SQS: Process messages from a queue for asynchronous tasks.
Amazon SNS: Respond to notifications (e.g., sending emails or SMS).
CloudWatch Events/EventBridge: Trigger Lambda functions on a schedule, or in response to AWS service events (e.g., an EC2 instance state change).
Kinesis: Process real-time streaming data.

These integrations form the backbone of modern, event-driven applications.

Quick Check

Test your knowledge of Lambda triggers!

인터랙티브 레슨에서 답해보세요

Recap: The Heart of Serverless Workflows

You've learned that Lambda functions are powerful, but they need triggers to come to life! These triggers are events from other AWS services that automatically invoke your function.

We explored how S3, DynamoDB Streams, and API Gateway can act as direct event sources, enabling you to build responsive, event-driven applications without managing servers. Understanding triggers is key to unlocking the full potential of serverless architecture!

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“Lambda 트리거와 통합” 강의는 무료인가요?

네 — “Lambda 트리거와 통합” 전체 내용을 이 웹사이트에서 무료로 읽을 수 있습니다. 인터랙티브하게 실습하려면(내장 코드 에디터와 24/7 AI 튜터), CoddyKit PRO로 업그레이드하면 AWS for Backend Developers (EC2, S3, RDS, Lambda) 강의 전체를 잠금 해제할 수 있습니다. AWS for Backend Developers (EC2, S3, RDS, Lambda) 강의에는 총 4개의 강의가 포함되어 있습니다.

“Lambda 트리거와 통합”에서 뭘 배우나요?

Lambda 함수를 S3, DynamoDB 및 API Gateway와 같은 다양한 AWS 서비스에 연결해 강력한 이벤트 기반 작업 흐름을 만듭니다. 브라우저에서 직접 실행하는 실습 코드로 AWS for Backend Developers (EC2, S3, RDS, Lambda)을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.

AWS for Backend Developers (EC2, S3, RDS, Lambda)을(를) 시작하는 데 경험이 필요한가요?

사전 경험은 필요하지 않습니다. CoddyKit의 AWS for Backend Developers (EC2, S3, RDS, Lambda)은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 3번째 강의입니다.

“Lambda 트리거와 통합” 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 AWS for Backend Developers (EC2, S3, RDS, Lambda) 강의에서 코드를 작성하고 실행할 수 있나요?

네. 모든 AWS for Backend Developers (EC2, S3, RDS, Lambda) 강의에는 내장 코드 에디터가 포함되어 있으므로, 브라우저에서 바로 실제 코드를 작성하고 실행한 후 즉시 AI 피드백을 받을 수 있습니다 — 로컬 설정이 필요 없습니다.

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