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aws-serverless

Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.

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AWS Serverless

Patterns

Lambda Handler Pattern

Proper Lambda function structure with error handling

When to use: ['Any Lambda function implementation', 'API handlers, event processors, scheduled tasks']

// Node.js Lambda Handler // handler.js

// Initialize outside handler (reused across invocations) const { DynamoDBClient } = require('@aws-sdk/client-dynamodb'); const { DynamoDBDocumentClient, GetCommand } = require('@aws-sdk/lib-dynamodb');

const client = new DynamoDBClient({}); const docClient = DynamoDBDocumentClient.from(client);

// Handler function exports.handler = async (event, context) => { // Optional: Don't wait for event loop to clear (Node.js) context.callbackWaitsForEmptyEventLoop = false;

try { // Parse input based on event source const body = typeof event.body === 'string' ? JSON.parse(event.body) : event.body;

// Business logic const result = await processRequest(body);

// Return API Gateway compatible response return { statusCode: 200, headers: { 'Content-Type': 'application/json', 'Access-Control-Allow-Origin': '*' }, body: JSON.stringify(result) }; } catch (error) { console.error('Error:', JSON.stringify({ error: error.message, stack: error.stack, requestId: context.awsRequestId }));

return { statusCode: error.statusCode || 500, headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ error: error.message || 'Internal server error' }) }; } };

async function processRequest(data) { // Your business logic here const result = await docClient.send(new GetCommand({ TableName: process.env.TABLE_NAME, Key: { id: data.id } })); return result.Item; }

Python Lambda Handler

handler.py

import json import os import logging import boto3 from botocore.exceptions import ClientError

Initialize outside handler (reused across invocations)

logger = logging.getLogger() logger.setLevel(logging.INFO)

dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['TABLE_NAME'])

def handler(event, context): try: # Parse i


### API Gateway Integration Pattern

REST API and HTTP API integration with Lambda

**When to use**: ['Building REST APIs backed by Lambda', 'Need HTTP endpoints for functions']
# template.yaml (SAM)
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31

Globals:
  Function:
    Runtime: nodejs20.x
    Timeout: 30
    MemorySize: 256
    Environment:
      Variables:
        TABLE_NAME: !Ref ItemsTable

Resources:
  # HTTP API (recommended for simple use cases)
  HttpApi:
    Type: AWS::Serverless::HttpApi
    Properties:
      StageName: prod
      CorsConfiguration:
        AllowOrigins:
          - "*"
        AllowMethods:
          - GET
          - POST
          - DELETE
        AllowHeaders:
          - "*"

  # Lambda Functions
  GetItemFunction:
    Type: AWS::Serverless::Function
    Properties:
      Handler: src/handlers/get.handler
      Events:
        GetItem:
          Type: HttpApi
          Properties:
            ApiId: !Ref HttpApi
            Path: /items/{id}
            Method: GET
      Policies:
        - DynamoDBReadPolicy:
            TableName: !Ref ItemsTable

  CreateItemFunction:
    Type: AWS::Serverless::Function
    Properties:
      Handler: src/handlers/create.handler
      Events:
        CreateItem:
          Type: HttpApi
          Properties:
            ApiId: !Ref HttpApi
            Path: /items
            Method: POST
      Policies:
        - DynamoDBCrudPolicy:
            TableName: !Ref ItemsTable

  # DynamoDB Table
  ItemsTable:
    Type: AWS::DynamoDB::Table
    Properties:
      AttributeDefinitions:
        - AttributeName: id
          AttributeType: S
      KeySchema:
        - AttributeName: id
          KeyType: HASH
      BillingMode: PAY_PER_REQUEST

Outputs:
  ApiUrl:
    Value: !Sub "https://${HttpApi}.execute-api.${AWS::Region}.amazonaws.com/prod"
// src/handlers/get.js
const { getItem } = require('../lib/dynamodb');

exports.handler = async (event) => {
  const id = event.pathParameters?.id;

  if (!id) {
    return {
      statusCode: 400,
      body: JSON.stringify({ error: 'Missing id parameter' })
    };
  }

  const item =

Event-Driven SQS Pattern

Lambda triggered by SQS for reliable async processing

When to use: ['Decoupled, asynchronous processing', 'Need retry logic and DLQ', 'Processing messages in batches']

template.yaml

Resources: ProcessorFunction: Type: AWS::Serverless::Function Properties: Handler: src/handlers/processor.handler Events: SQSEvent: Type: SQS Properties: Queue: !GetAtt ProcessingQueue.Arn BatchSize: 10 FunctionResponseTypes:

  • ReportBatchItemFailures # Partial batch failure handling

ProcessingQueue: Type: AWS::SQS::Queue Properties: VisibilityTimeout: 180 # 6x Lambda timeout RedrivePolicy: deadLetterTargetArn: !GetAtt DeadLetterQueue.Arn maxReceiveCount: 3

DeadLetterQueue: Type: AWS::SQS::Queue Properties: MessageRetentionPeriod: 1209600 # 14 days

// src/handlers/processor.js exports.handler = async (event) => { const batchItemFailures = [];

for (const record of event.Records) { try { const body = JSON.parse(record.body); await processMessage(body); } catch (error) { console.error(Failed to process message ${record.messageId}:, error); // Report this item as failed (will be retried) batchItemFailures.push({ itemIdentifier: record.messageId }); } }

// Return failed items for retry return { batchItemFailures }; };

async function processMessage(message) { // Your processing logic console.log('Processing:', message);

// Simulate work await saveToDatabase(message); }

Python version

import json import logging

logger = logging.getLogger()

def handler(event, context): batch_item_failures = []

for record in event['Records']: try: body = json.loads(record['body']) process_message(body) except Exception as e: logger.error(f"Failed to process {record['messageId']}: {e}") batch_item_failures.append({ 'itemIdentifier': record['messageId'] })

return {'batchItemFailures': batch_ite


## Anti-Patterns

### ❌ Monolithic Lambda

**Why bad**: Large deployment packages cause slow cold starts.
Hard to scale individual operations.
Updates affect entire system.

### ❌ Large Dependencies

**Why bad**: Increases deployment package size.
Slows down cold starts significantly.
Most of SDK/library may be unused.

### ❌ Synchronous Calls in VPC

**Why bad**: VPC-attached Lambdas have ENI setup overhead.
Blocking DNS lookups or connections worsen cold starts.

## ⚠️ Sharp Edges

| Issue | Severity | Solution |
|-------|----------|----------|
| Issue | high | ## Measure your INIT phase |
| Issue | high | ## Set appropriate timeout |
| Issue | high | ## Increase memory allocation |
| Issue | medium | ## Verify VPC configuration |
| Issue | medium | ## Tell Lambda not to wait for event loop |
| Issue | medium | ## For large file uploads |
| Issue | high | ## Use different buckets/prefixes |
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