Serverless AWS Lambda Development · 课时

在 VPC 中使用 Lambda 访问私有资源

了解如何配置 Lambda 函数，使其在 VPC 中运行，从而安全访问数据库和内部服务等私有资源

在 VPC 中使用 Lambda 访问私有资源 是 CoddyKit 上的免费 Serverless AWS Lambda Development 课时。这是第 1 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 Serverless AWS Lambda Development 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Serverless AWS Lambda Development 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

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.

常见问题解答

「在 VPC 中使用 Lambda 访问私有资源」课时是免费的吗？

是的 — 「在 VPC 中使用 Lambda 访问私有资源」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Serverless AWS Lambda Development 课程的其余内容，请升级到 CoddyKit PRO。 Serverless AWS Lambda Development 课程共包含 4 节课。

「在 VPC 中使用 Lambda 访问私有资源」这节课中我会学到什么？

了解如何配置 Lambda 函数，使其在 VPC 中运行，从而安全访问数据库和内部服务等私有资源你通过在浏览器中直接运行的动手代码来练习 Serverless AWS Lambda Development，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Serverless AWS Lambda Development 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Serverless AWS Lambda Development 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 1 节课，共 4 节。

「在 VPC 中使用 Lambda 访问私有资源」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Serverless AWS Lambda Development 课中编写并运行代码吗？

能。每节 Serverless AWS Lambda Development 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

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