Serverless AWS Lambda Development · レッスン

プライベートリソース向けVPC内のLambda

Lambda関数をVPC内で動作するよう設定し、データベースや内部サービスなどのプライベートリソースへ安全にアクセスする方法を理解します。

「プライベートリソース向けVPC内のLambda」はCoddyKit上の無料Serverless AWS Lambda Developmentレッスンです。これはレッスン1/4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Serverless AWS Lambda Development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。 Serverless AWS Lambda Development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。

Why Lambda Needs a VPC

By default, AWS Lambda functions run in a network managed by AWS. This network provides internet access but isolates your function from your private AWS resources.

To securely access resources like databases (e.g., Amazon RDS, DynamoDB tables in a VPC) or internal services that are not publicly available, your Lambda function needs to operate within your own Virtual Private Cloud (VPC).

Your Private Cloud Corner

A Virtual Private Cloud (VPC) is like your own isolated, private network within AWS. You define its IP address range, subnets, and network gateways.

Subnets: Divisions within your VPC. Private subnets host resources that shouldn't be publicly accessible.
Security Groups: Act as virtual firewalls, controlling inbound and outbound traffic for resources within your VPC.

Accessing Private Resources

Imagine you have a database that holds sensitive customer data. You wouldn't want it exposed to the public internet.

If your Lambda function needs to read from or write to such a database, or connect to an EC2 instance, or an internal API endpoint that resides only within your VPC, then your Lambda function must also be placed inside that VPC.

Lambda's Network Interface

When you configure a Lambda function to run within a VPC, AWS creates an Elastic Network Interface (ENI) for your function in the specified subnets.

This ENI provides your Lambda function with a private IP address and allows it to communicate with other resources in your VPC, just like an EC2 instance would.

Subnets & Security Groups

When attaching Lambda to a VPC, you specify:

Subnets: At least two private subnets in different Availability Zones for high availability. Lambda functions will be deployed across these.
Security Groups: One or more security groups to control what network traffic is allowed to and from your Lambda function. Ensure they permit communication with your private resources.

Attaching Lambda to VPC

In the AWS Management Console, when creating or configuring a Lambda function, you'll find a "VPC" section under "Advanced settings" or "Configuration".

Here, you select your desired VPC, choose at least two subnets (for redundancy), and assign appropriate security groups. AWS handles the ENI creation automatically.

A Function Ready for VPC

This simple Python Lambda function doesn't actually connect to a database, but it shows the structure of a function that could run within a VPC and interact with private resources. If it were in a VPC, it could initiate a connection to a private database.

Try running this example:

import json

def lambda_handler(event, context):
    # This function would typically connect to a private resource
    # if configured within a VPC.
    # For example:
    # import pymysql # Database connector
    # conn = pymysql.connect(host='your-private-db-endpoint', user='admin', password='password', database='mydatabase')
    # with conn.cursor() as cursor:
    #     cursor.execute("SELECT * FROM users")
    #     result = cursor.fetchall()

    message = "Hello from a Lambda function in a VPC context!"
    print(message)

    return {
        'statusCode': 200,
        'body': json.dumps(message)
    }

Outbound Internet from VPC

If your Lambda function in a private subnet needs to access the internet (e.g., to call external APIs, fetch updates), it won't have direct access.

You'll need a NAT Gateway (Network Address Translation Gateway) deployed in a public subnet within your VPC. Traffic from your private subnets will route through the NAT Gateway to reach the internet.

VPC Endpoints for AWS Services

For accessing certain AWS services (like S3, DynamoDB, SQS) from a Lambda in a private subnet, you can use VPC Endpoints instead of a NAT Gateway.

VPC Endpoints allow your Lambda to communicate with these services privately, without traversing the public internet, which can be more secure and cost-effective.

Important Considerations

While powerful, running Lambda in a VPC has implications:

Cold Starts: The time it takes for Lambda to create an ENI can sometimes increase cold start latency.
IP Address Management: Each ENI consumes a private IP address from your subnet, so ensure you have sufficient IP space.
Network Overhead: Managing subnets, security groups, and potentially NAT Gateways adds configuration complexity.

Quick Check: VPC Benefits

You've learned why and how Lambda functions can operate within a VPC. Let's test your understanding.

Lesson Summary

In this lesson, you learned that configuring Lambda functions within a VPC enables them to securely access private resources like databases and internal services.

We covered how Lambda uses Elastic Network Interfaces (ENIs) to connect to subnets and security groups, and the considerations for internet access (NAT Gateway) and private AWS service access (VPC Endpoints). This setup is crucial for building secure, enterprise-grade serverless applications.

よくある質問

「プライベートリソース向けVPC内のLambda」レッスンは無料ですか？

はい。「プライベートリソース向けVPC内のLambda」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）、Serverless AWS Lambda Development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。 Serverless AWS Lambda Developmentコースには全4レッスンが含まれています。

「プライベートリソース向けVPC内のLambda」で何を学びますか？

Lambda関数をVPC内で動作するよう設定し、データベースや内部サービスなどのプライベートリソースへ安全にアクセスする方法を理解します。ブラウザで直接実行するハンズオンコードでServerless AWS Lambda Development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。

Serverless AWS Lambda Development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Serverless AWS Lambda Development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1/4です。

「プライベートリソース向けVPC内のLambda」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Serverless AWS Lambda Development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Serverless AWS Lambda Development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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