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']

javascript

// 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

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']

javascript

# 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']

yaml

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

javascript

// 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

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