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AWSLambda函数Skill aws-lambda-functions

本文档提供了关于如何创建和部署AWS Lambda函数的详细指南，包括事件源、权限、层和环境配置等。适用于无服务器计算，无需管理服务器，适用于API端点、计划任务、实时文件处理等多种场景。

Serverless 0 次安装 0 次浏览 更新于 3/3/2026

name: aws-lambda-functions description: 创建并部署无服务器函数，使用AWS Lambda和事件源、权限、层以及环境配置。适用于事件驱动计算而无需管理服务器。

AWS Lambda 函数

概览

AWS Lambda 允许您无需预置或管理服务器即可运行代码。使用事件驱动触发器构建无服务器应用程序，仅支付消耗的计算时间，并根据工作负载自动扩展。

使用场景

  • API端点和Webhook
  • 计划批处理作业和数据处理
  • 实时文件处理（S3上传）
  • 事件驱动工作流（SNS、SQS）
  • 微服务和后端API
  • 数据转换和ETL作业
  • IoT和传感器数据处理
  • WebSocket连接

实施示例

1. 使用AWS CLI的基本Lambda函数

# 创建Lambda执行角色
aws iam create-role \
  --role-name lambda-execution-role \
  --assume-role-policy-document '{
    "Version": "2012-10-17",
    "Statement": [{
      "Effect": "Allow",
      "Principal": {"Service": "lambda.amazonaws.com"},
      "Action": "sts:AssumeRole"
    }]
  }'

# 附加基本执行策略
aws iam attach-role-policy \
  --role-name lambda-execution-role \
  --policy-arn arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole

# 从ZIP创建函数
zip function.zip index.js
aws lambda create-function \
  --function-name my-function \
  --runtime nodejs18.x \
  --role arn:aws:iam::ACCOUNT:role/lambda-execution-role \
  --handler index.handler \
  --zip-file fileb://function.zip \
  --timeout 30 \
  --memory-size 256 \
  --environment Variables={ENV=production,DB_HOST=db.example.com}

# 调用函数
aws lambda invoke \
  --function-name my-function \
  --payload '{"name":"John","age":30}' \
  response.json

2. 使用Node.js的Lambda函数

// index.js
exports.handler = async (event) => {
  console.log('Event:', JSON.stringify(event));

  try {
    // 解析不同的事件源
    const body = typeof event.body === 'string'
      ? JSON.parse(event.body)
      : event.body || {};

    // 处理S3事件
    if (event.Records && event.Records[0].s3) {
      const bucket = event.Records[0].s3.bucket.name;
      const key = event.Records[0].s3.object.key;
      console.log(`Processing S3 object: ${bucket}/${key}`);
    }

    // 数据库查询模拟
    const results = await queryDatabase(body);

    return {
      statusCode: 200,
      headers: {
        'Content-Type': 'application/json',
        'Access-Control-Allow-Origin': '*'
      },
      body: JSON.stringify({
        message: 'Success',
        data: results
      })
    };
  } catch (error) {
    console.error('Error:', error);
    return {
      statusCode: 500,
      body: JSON.stringify({ error: error.message })
    };
  }
};

async function queryDatabase(params) {
  // 模拟数据库调用
  return { items: [] };
}

3. 使用Terraform的Lambda部署

# main.tf
terraform {
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
}

provider "aws" {
  region = var.aws_region
}

# Lambda执行角色
resource "aws_iam_role" "lambda_role" {
  name = "lambda-execution-role"

  assume_role_policy = jsonencode({
    Version = "2012-10-17"
    Statement = [{
      Action = "sts:AssumeRole"
      Effect = "Allow"
      Principal = {
        Service = "lambda.amazonaws.com"
      }
    }]
  })
}

# CloudWatch日志策略
resource "aws_iam_role_policy_attachment" "lambda_logs" {
  role       = aws_iam_role.lambda_role.name
  policy_arn = "arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole"
}

# S3 Lambda层（依赖项）
resource "aws_lambda_layer_version" "dependencies" {
  filename            = "layer.zip"
  layer_name          = "nodejs-dependencies"
  compatible_runtimes = ["nodejs18.x"]
}

# Lambda函数
resource "aws_lambda_function" "api_handler" {
  filename      = "lambda.zip"
  function_name = "api-handler"
  role          = aws_iam_role.lambda_role.arn
  handler       = "index.handler"
  runtime       = "nodejs18.x"
  timeout       = 30
  memory_size   = 256

  layers = [aws_lambda_layer_version.dependencies.arn]

  environment {
    variables = {
      STAGE = "production"
      DB_HOST = var.database_host
    }
  }

  depends_on = [aws_iam_role_policy_attachment.lambda_logs]
}

# API网关触发器
resource "aws_lambda_permission" "api_gateway" {
  statement_id  = "AllowAPIGatewayInvoke"
  action        = "lambda:InvokeFunction"
  function_name = aws_lambda_function.api_handler.function_name
  principal     = "apigateway.amazonaws.com"
}

# S3触发器
resource "aws_lambda_permission" "s3_trigger" {
  statement_id  = "AllowS3Invoke"
  action        = "lambda:InvokeFunction"
  function_name = aws_lambda_function.api_handler.function_name
  principal     = "s3.amazonaws.com"
  source_arn    = aws_s3_bucket.upload_bucket.arn
}

resource "aws_s3_bucket_notification" "bucket_notification" {
  bucket      = aws_s3_bucket.upload_bucket.id
  depends_on  = [aws_lambda_permission.s3_trigger]

  lambda_function {
    lambda_function_arn = aws_lambda_function.api_handler.arn
    events              = ["s3:ObjectCreated:*"]
    filter_prefix       = "uploads/"
    filter_suffix       = ".jpg"
  }
}

4. 使用SAM（Serverless Application Model）的Lambda

# template.yaml
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31

Globals:
  Function:
    Timeout: 30
    MemorySize: 256
    Runtime: nodejs18.x
    Tracing: Active

Parameters:
  Environment:
    Type: String
    Default: dev
    AllowedValues: [dev, prod]

Resources:
  # Lambda函数
  MyFunction:
    Type: AWS::Serverless::Function
    Properties:
      FunctionName: !Sub '${Environment}-my-function'
      CodeUri: src/
      Handler: index.handler
      Architectures:
        - x86_64
      Environment:
        Variables:
          STAGE: !Ref Environment
      Policies:
        - DynamoDBCrudPolicy:
            TableName: !Ref DataTable
        - S3CrudPolicy:
            BucketName: !Ref DataBucket
      Events:
        ApiEvent:
          Type: Api
          Properties:
            Path: /api/{proxy+}
            Method: ANY
            RestApiId: !Ref MyApi
        S3Upload:
          Type: S3
          Properties:
            Bucket: !Ref DataBucket
            Events: s3:ObjectCreated:*
            Filter:
              S3Key:
                Rules:
                  - Name: prefix
                    Value: uploads/

  # DynamoDB表
  DataTable:
    Type: AWS::DynamoDB::Table
    Properties:
      TableName: !Sub '${Environment}-data'
      BillingMode: PAY_PER_REQUEST
      AttributeDefinitions:
        - AttributeName: id
          AttributeType: S
      KeySchema:
        - AttributeName: id
          KeyType: HASH

  # S3桶
  DataBucket:
    Type: AWS::S3::Bucket
    Properties:
      BucketName: !Sub '${Environment}-data-${AWS::AccountId}'
      VersioningConfiguration:
        Status: Enabled

  # API网关
  MyApi:
    Type: AWS::Serverless::Api
    Properties:
      Name: !Sub '${Environment}-api'
      StageName: !Ref Environment
      Cors:
        AllowMethods: "'*'"
        AllowHeaders: "'Content-Type,Authorization'"
        AllowOrigin: "'*'"

Outputs:
  FunctionArn:
    Value: !GetAtt MyFunction.Arn
  ApiEndpoint:
    Value: !Sub 'https://${MyApi}.execute-api.${AWS::Region}.amazonaws.com'

5. 代码共享的Lambda层

# 创建层目录结构
mkdir -p layer/nodejs/node_modules
cd layer/nodejs

# 安装依赖项
npm install lodash axios moment

# 返回并创建zip
cd ..
zip -r layer.zip .

# 上传层
aws lambda publish-layer-version \
  --layer-name shared-utils \
  --zip-file fileb://layer.zip \
  --compatible-runtimes nodejs18.x

最佳实践

✅ DO

  • 使用环境变量进行配置
  • 实施适当的错误处理和日志记录
  • 优化包大小和依赖项
  • 设置适当的超时和内存
  • 使用Lambda层共享代码
  • 实施并发限制
  • 启用X-Ray跟踪以进行调试
  • 为关键函数使用预留并发

❌ DON’T

  • 在代码中存储敏感数据
  • 创建长时间运行的操作（>15分钟）
  • 忽略冷启动优化
  • 忘记处理并发执行
  • 忽略CloudWatch指标
  • 无谓地使用太多内存

监控与故障排除

  • CloudWatch日志用于应用程序日志记录
  • CloudWatch指标用于持续时间、错误、节流
  • X-Ray跟踪用于性能分析
  • 死信队列用于失败的消息
  • 报警用于错误和节流

资源