AWS for Backend Developers (EC2, S3, RDS, Lambda) · レッスン

初めての Lambda 関数を作成する

シンプルな Lambda 関数を記述・デプロイし、ランタイム、メモリ、実行ロールを設定します。

「初めての Lambda 関数を作成する」はCoddyKit上の無料AWS for Backend Developers (EC2, S3, RDS, Lambda)レッスンです。これはレッスン2/4です。下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。これはAWS for Backend Developers (EC2, S3, RDS, Lambda)学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 AWS for Backend Developers (EC2, S3, RDS, Lambda)コースには全4レッスンが含まれています。

このレッスンの一部はまだ翻訳されておらず、英語で表示されています。

Your First Lambda Function

Time to build your first serverless function! In this lesson, we'll write a simple AWS Lambda function that runs your code without managing servers.

We'll cover its basic structure, how to choose a runtime, and essential configurations like memory and execution roles. Get ready to deploy!

The Core: Your Lambda Handler

Every Lambda function needs a 'handler' function. This is the entry point where AWS Lambda starts executing your code. It typically receives two arguments:

event: Contains the data that triggered the invocation.
context: Provides runtime information about the invocation, function, and execution environment.

Think of the handler as the 'main' method for your serverless code.

Pick Your Language: Lambda Runtimes

AWS Lambda supports many programming languages, called 'runtimes.' You choose the one your function code is written in. The runtime determines the execution environment and how your handler is called.

Python: Great for scripting, data processing, and machine learning.
Node.js: Ideal for real-time applications, APIs, and microservices.
Java: Good for enterprise applications, high performance, and existing JVM ecosystems.
Go, C#, Ruby, Custom Runtimes: More options for diverse needs and specific use cases.

Hello Lambda: A Basic Python Example

Let's write a very simple Python Lambda function. This function will take an input name from the event and return a greeting. Try running it to see the output!

import json

def lambda_handler(event, context):
    # event is a dictionary containing invocation data
    # context provides runtime info (e.g., function name, memory limit)

    # We expect 'name' in the event payload
    name = event.get('name', 'World')
    message = f"Hello, {name}!"

    # Lambda functions often return a dictionary, which AWS converts to JSON
    return {
        'statusCode': 200,
        'body': json.dumps(message)
    }

# --- Local Test Simulation ---
if __name__ == "__main__":
    # Simulate an event payload
    test_event = {"name": "CoddyKit User"}
    
    # Simulate a dummy context object
    class Context:
        def __init__(self):
            self.function_name = "my-test-function"
            self.memory_limit_in_mb = 128
            self.invoked_function_arn = "arn:aws:lambda:us-east-1:123456789012:function:my-test-function"
            self.aws_request_id = "test-request-id-123"

    test_context = Context()

    # Call the handler
    response = lambda_handler(test_event, test_context)
    
    # Print the response for local verification
    print(f"Status Code: {response['statusCode']}")
    print(f"Body: {json.loads(response['body'])}")

    # Test without a name
    test_event_no_name = {}
    response_no_name = lambda_handler(test_event_no_name, test_context)
    print(f"\nStatus Code (no name): {response_no_name['statusCode']}")
    print(f"Body (no name): {json.loads(response_no_name['body'])}")

Your Function's Input: The Event

The event object is a Python dictionary (or JSON object in other runtimes) that contains the data passed to your function. This data comes from the service that triggered your Lambda.

If triggered by an API Gateway: It contains HTTP method, headers, body.
If triggered by S3: It contains details about the S3 bucket and object.
If invoked directly: It contains whatever JSON payload you passed.

Your function processes this input to perform its task.

Runtime Details: The Context

The context object provides information about the invocation, function, and execution environment. It's useful for logging and making runtime decisions.

function_name: The name of your Lambda function.
aws_request_id: A unique ID for the invocation.
memory_limit_in_mb: The memory allocated to the function.
get_remaining_time_in_millis(): How much time is left before the function times out.

You can use this for advanced error handling or logging within your function.

Permissions with IAM Execution Roles

A Lambda function needs permission to interact with other AWS services. This is managed by an IAM Role, specifically called the "execution role."

The role defines what actions your Lambda can perform (e.g., write logs to CloudWatch, read from S3).
You attach policies to this role, specifying permissions.
Without the correct permissions, your function will fail when trying to access other AWS resources.

Always follow the principle of least privilege, granting only the necessary permissions.

Fine-Tuning: Memory & Timeout

When you create a Lambda function, you configure several settings that impact its performance and cost:

Memory: Defines the RAM allocated (e.g., 128MB to 10GB). More memory often means more CPU power too.
Timeout: The maximum time your function can run (e.g., 3 seconds to 15 minutes). If it exceeds this, Lambda stops it.
Environment Variables: Key-value pairs accessible to your code, great for configuration without changing code.

Choosing appropriate settings is crucial for efficiency and cost optimization.

Getting Your Function Live

Once your code is ready, you deploy it to AWS Lambda. Here's a high-level overview:

Package your code: Zip your code and any dependencies into a deployment package.
Upload: Use the AWS Console, AWS CLI, or an Infrastructure as Code (IaC) tool like AWS SAM or CloudFormation.
Test: Invoke your function directly from the Lambda console with test events, or trigger it via an integrated service like API Gateway or S3.

The console provides a quick way to get started and test your function immediately.

Quick Check: Lambda Handler

Consider the basic structure of a Python Lambda handler:

def lambda_handler(event, context):
    # ... your code ...
    return response

What is the primary purpose of the event parameter?

Recap: Your First Serverless Step

Great job! You've learned the fundamentals of building a Lambda function:

Every Lambda needs a handler function as its entry point.
You choose a runtime (like Python) for your code.
The event object carries input data, and context provides runtime info.
An IAM execution role grants your function necessary permissions.
You configure settings like memory and timeout for performance and cost.

This is your foundation for building powerful serverless applications!

よくある質問

「初めての Lambda 関数を作成する」レッスンは無料ですか？

はい。「初めての Lambda 関数を作成する」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し（組み込みコードエディタと24時間対応のAIチューター）、AWS for Backend Developers (EC2, S3, RDS, Lambda)コースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 AWS for Backend Developers (EC2, S3, RDS, Lambda)コースには全4レッスンが含まれています。

「初めての Lambda 関数を作成する」で何を学びますか？

シンプルな Lambda 関数を記述・デプロイし、ランタイム、メモリ、実行ロールを設定します。ブラウザで直接実行するハンズオンコードでAWS for Backend Developers (EC2, S3, RDS, Lambda)を演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。

AWS for Backend Developers (EC2, S3, RDS, Lambda)を始めるのに経験は必要ですか？

事前経験は必要ありません。CoddyKitのAWS for Backend Developers (EC2, S3, RDS, Lambda)は初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。これはレッスン2/4です。

「初めての Lambda 関数を作成する」レッスンにはどのくらい時間がかかりますか？

ほとんどのCoddyKitレッスンは約5～10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。

このAWS for Backend Developers (EC2, S3, RDS, Lambda)レッスンでコードを書いて実行できますか？

はい。すべてのAWS for Backend Developers (EC2, S3, RDS, Lambda)レッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。

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