aws-serverless

CategoryGeneral
AuthorAgentic Awesome Skills 社区
LicenseMIT
Rating4.60/5
Uses14.1K

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.

Principles

  • Right-size memory and timeout (measure before optimizing)
  • Minimize cold starts for latency-sensitive workloads
  • Use SnapStart for Java/.NET functions
  • Prefer HTTP API over REST API for simple use cases
  • Design for failure with DLQs and retries
  • Keep deployment packages small
  • Use environment variables for configuration
  • Implement structured logging with correlation IDs

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 input
body = json.loads(event.get('body', '{}')) if isinstance(event.get('body'), str) else event.get('body', {})

# Business logic
result = process_request(body)

return {
'statusCode': 200,
'headers': {
'Content-Type': 'application/json',
'Access-Control-Allow-Origin': '*'
},
'body': json.dumps(result)
}

except ClientError as e:
logger.error(f"DynamoDB error: {e.response['Error']['Message']}")
return error_response(500, 'Database error')

except json.JSONDecodeError:
return error_response(400, 'Invalid JSON')

except Exception as e:
logger.error(f"Unexpected error: {str(e)}", exc_info=True)
return error_response(500, 'Internal server error')

def process_request(data):
response = table.get_item(Key={'id': data['id']})
return response.get('Item')

def error_response(status_code, message):
return {
'statusCode': status_code,
'headers': {'Content-Type': 'application/json'},
'body': json.dumps({'error': message})
}

Best_practices

  • Initialize clients outside handler (reused across warm invocations)
  • Always return proper API Gateway response format
  • Log with structured JSON for CloudWatch Insights
  • Include request ID in error logs for tracing

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

yaml
# 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"

javascript
// 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 = await getItem(id);

if (!item) {
return {
statusCode: 404,
body: JSON.stringify({ error: 'Item not found' })
};
}

return {
statusCode: 200,
body: JSON.stringify(item)
};
};

Structure

project/
├── template.yaml # SAM template
├── src/
│ ├── handlers/
│ │ ├── get.js
│ │ ├── create.js
│ │ └── delete.js
│ └── lib/
│ └── dynamodb.js
└── events/
└── event.json # Test events

Api_comparison

  • Http_api:
- Lower latency (~10ms) - Lower cost (50-70% cheaper) - Simpler, fewer features - Best for: Most REST APIs
  • Rest_api:
- More features (caching, request validation, WAF) - Usage plans and API keys - Request/response transformation - Best for: Complex APIs, enterprise features

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_item_failures}

Best_practices

  • Set VisibilityTimeout to 6x Lambda timeout
  • Use ReportBatchItemFailures for partial batch failure
  • Always configure a DLQ for poison messages
  • Process messages idempotently

DynamoDB Streams Pattern

React to DynamoDB table changes with Lambda

When to use: Real-time reactions to data changes,Cross-region replication,Audit logging, notifications

yaml
# template.yaml
Resources:
  ItemsTable:
    Type: AWS::DynamoDB::Table
    Properties:
      TableName: items
      AttributeDefinitions:
        - AttributeName: id
          AttributeType: S
      KeySchema:
        - AttributeName: id
          KeyType: HASH
      BillingMode: PAY_PER_REQUEST
      StreamSpecification:
        StreamViewType: NEW_AND_OLD_IMAGES

StreamProcessorFunction:
Type: AWS::Serverless::Function
Properties:
Handler: src/handlers/stream.handler
Events:
Stream:
Type: DynamoDB
Properties:
Stream: !GetAtt ItemsTable.StreamArn
StartingPosition: TRIM_HORIZON
BatchSize: 100
MaximumRetryAttempts: 3
DestinationConfig:
OnFailure:
Destination: !GetAtt StreamDLQ.Arn

StreamDLQ:
Type: AWS::SQS::Queue

javascript
// src/handlers/stream.js
exports.handler = async (event) => {
  for (const record of event.Records) {
    const eventName = record.eventName;  // INSERT, MODIFY, REMOVE

// Unmarshall DynamoDB format to plain JS objects
const newImage = record.dynamodb.NewImage
? unmarshall(record.dynamodb.NewImage)
: null;
const oldImage = record.dynamodb.OldImage
? unmarshall(record.dynamodb.OldImage)
: null;

console.log(${eventName}: , { newImage, oldImage });

switch (eventName) {
case 'INSERT':
await handleInsert(newImage);
break;
case 'MODIFY':
await handleModify(oldImage, newImage);
break;
case 'REMOVE':
await handleRemove(oldImage);
break;
}
}
};

// Use AWS SDK v3 unmarshall
const { unmarshall } = require('@aws-sdk/util-dynamodb');

Stream_view_types

  • KEYS_ONLY: Only key attributes
  • NEW_IMAGE: After modification
  • OLD_IMAGE: Before modification
  • NEW_AND_OLD_IMAGES: Both before and after

Cold Start Optimization Pattern

Minimize Lambda cold start latency

When to use: Latency-sensitive applications,User-facing APIs,High-traffic functions

1. Optimize Package Size

javascript
// Use modular AWS SDK v3 imports
// GOOD - only imports what you need
const { DynamoDBClient } = require('@aws-sdk/client-dynamodb');
const { DynamoDBDocumentClient, GetCommand } = require('@aws-sdk/lib-dynamodb');

// BAD - imports entire SDK
const AWS = require('aws-sdk'); // Don't do this!

2. Use SnapStart (Java/.NET)

yaml
# template.yaml
Resources:
  JavaFunction:
    Type: AWS::Serverless::Function
    Properties:
      Handler: com.example.Handler::handleRequest
      Runtime: java21
      SnapStart:
        ApplyOn: PublishedVersions  # Enable SnapStart
      AutoPublishAlias: live

3. Right-size Memory

yaml
# More memory = more CPU = faster init
Resources:
  FastFunction:
    Type: AWS::Serverless::Function
    Properties:
      MemorySize: 1024  # 1GB gets full vCPU
      Timeout: 30

4. Provisioned Concurrency (when needed)

yaml
Resources:
  CriticalFunction:
    Type: AWS::Serverless::Function
    Properties:
      Handler: src/handlers/critical.handler
      AutoPublishAlias: live

ProvisionedConcurrency:
Type: AWS::Lambda::ProvisionedConcurrencyConfig
Properties:
FunctionName: !Ref CriticalFunction
Qualifier: live
ProvisionedConcurrentExecutions: 5

5. Keep Init Light

python
# GOOD - Lazy initialization
_table = None

def get_table():
global _table
if _table is None:
dynamodb = boto3.resource('dynamodb')
_table = dynamodb.Table(os.environ['TABLE_NAME'])
return _table

def handler(event, context):
table = get_table() # Only initializes on first use
# ...

Optimization_priority

  • 1: Reduce package size (biggest impact)
  • 2: Use SnapStart for Java/.NET
  • 3: Increase memory for faster init
  • 4: Delay heavy imports
  • 5: Provisioned concurrency (last resort)

SAM Local Development Pattern

Local testing and debugging with SAM CLI

When to use: Local development and testing,Debugging Lambda functions,Testing API Gateway locally

bash
# Install SAM CLI
pip install aws-sam-cli

Initialize new project

sam init --runtime nodejs20.x --name my-api

Build the project

sam build

Run locally

sam local start-api

Invoke single function

sam local invoke GetItemFunction --event events/get.json

Local debugging (Node.js with VS Code)

sam local invoke --debug-port 5858 GetItemFunction

Deploy

sam deploy --guided
json
// events/get.json (test event)
{
  "pathParameters": {
    "id": "123"
  },
  "httpMethod": "GET",
  "path": "/items/123"
}
json
// .vscode/launch.json (for debugging)
{
  "version": "0.2.0",
  "configurations": [
    {
      "name": "Attach to SAM CLI",
      "type": "node",
      "request": "attach",
      "address": "localhost",
      "port": 5858,
      "localRoot": "${workspaceRoot}/src",
      "remoteRoot": "/var/task/src",
      "protocol": "inspector"
    }
  ]
}

Commands

  • Sam_build: Build Lambda deployment packages
  • Sam_local_start_api: Start local API Gateway
  • Sam_local_invoke: Invoke single function
  • Sam_deploy: Deploy to AWS
  • Sam_logs: Tail CloudWatch logs

CDK Serverless Pattern

Infrastructure as code with AWS CDK

When to use: Complex infrastructure beyond Lambda,Prefer programming languages over YAML,Need reusable constructs

typescript
// lib/api-stack.ts
import * as cdk from 'aws-cdk-lib';
import * as lambda from 'aws-cdk-lib/aws-lambda';
import * as apigateway from 'aws-cdk-lib/aws-apigateway';
import * as dynamodb from 'aws-cdk-lib/aws-dynamodb';
import { Construct } from 'constructs';

export class ApiStack extends cdk.Stack {
constructor(scope: Construct, id: string, props?: cdk.StackProps) {
super(scope, id, props);

// DynamoDB Table
const table = new dynamodb.Table(this, 'ItemsTable', {
partitionKey: { name: 'id', type: dynamodb.AttributeType.STRING },
billingMode: dynamodb.BillingMode.PAY_PER_REQUEST,
removalPolicy: cdk.RemovalPolicy.DESTROY, // For dev only
});

// Lambda Function
const getItemFn = new lambda.Function(this, 'GetItemFunction', {
runtime: lambda.Runtime.NODEJS_20_X,
handler: 'get.handler',
code: lambda.Code.fromAsset('src/handlers'),
environment: {
TABLE_NAME: table.tableName,
},
memorySize: 256,
timeout: cdk.Duration.seconds(30),
});

// Grant permissions
table.grantReadData(getItemFn);

// API Gateway
const api = new apigateway.RestApi(this, 'ItemsApi', {
restApiName: 'Items Service',
defaultCorsPreflightOptions: {
allowOrigins: apigateway.Cors.ALL_ORIGINS,
allowMethods: apigateway.Cors.ALL_METHODS,
},
});

const items = api.root.addResource('items');
const item = items.addResource('{id}');

item.addMethod('GET', new apigateway.LambdaIntegration(getItemFn));

// Output API URL
new cdk.CfnOutput(this, 'ApiUrl', {
value: api.url,
});
}
}

bash
# CDK commands
npm install -g aws-cdk
cdk init app --language typescript
cdk synth    # Generate CloudFormation
cdk diff     # Show changes
cdk deploy   # Deploy to AWS

Sharp Edges

Cold Start INIT Phase Now Billed (Aug 2025)

Severity: HIGH

Situation: Running Lambda functions in production

Symptoms:
Unexplained increase in Lambda costs (10-50% higher).
Bill includes charges for function initialization.
Functions with heavy startup logic cost more than expected.

Why this breaks:
As of August 1, 2025, AWS bills the INIT phase the same way it bills
invocation duration. Previously, cold start initialization wasn't billed
for the full duration.

This affects functions with:

  • Heavy dependency loading (large packages)

  • Slow initialization code

  • Frequent cold starts (low traffic or poor concurrency)

Cold starts now directly impact your bill, not just latency.

Recommended fix:

Measure your INIT phase

bash
# Check CloudWatch Logs for INIT_REPORT

Look for Init Duration in milliseconds

Example log line:

INIT_REPORT Init Duration: 423.45 ms

Reduce INIT duration

javascript
// 1. Minimize package size
// Use tree shaking, exclude dev dependencies
// npm prune --production

// 2. Lazy load heavy dependencies
let heavyLib = null;
function getHeavyLib() {
if (!heavyLib) {
heavyLib = require('heavy-library');
}
return heavyLib;
}

// 3. Use AWS SDK v3 modular imports
const { S3Client } = require('@aws-sdk/client-s3');
// NOT: const AWS = require('aws-sdk');

Use SnapStart for Java/.NET

yaml
Resources:
  JavaFunction:
    Type: AWS::Serverless::Function
    Properties:
      Runtime: java21
      SnapStart:
        ApplyOn: PublishedVersions

Monitor cold start frequency

javascript
// Track cold starts with custom metric
let isColdStart = true;

exports.handler = async (event) => {
if (isColdStart) {
console.log('COLD_START');
// CloudWatch custom metric here
isColdStart = false;
}
// ...
};

Lambda Timeout Misconfiguration

Severity: HIGH

Situation: Running Lambda functions, especially with external calls

Symptoms:
Function times out unexpectedly.
"Task timed out after X seconds" in logs.
Partial processing with no response.
Silent failures with no error caught.

Why this breaks:
Default Lambda timeout is only 3 seconds. Maximum is 15 minutes.

Common timeout causes:

  • Default timeout too short for workload

  • Downstream service taking longer than expected

  • Network issues in VPC

  • Infinite loops or blocking operations

  • S3 downloads larger than expected

Lambda terminates at timeout without graceful shutdown.

Recommended fix:

Set appropriate timeout

yaml
# template.yaml
Resources:
  MyFunction:
    Type: AWS::Serverless::Function
    Properties:
      Timeout: 30  # Seconds (max 900)
      # Set to expected duration + buffer

Implement timeout awareness

javascript
exports.handler = async (event, context) => {
  // Get remaining time
  const remainingTime = context.getRemainingTimeInMillis();

// If running low on time, fail gracefully
if (remainingTime < 5000) {
console.warn('Running low on time, aborting');
throw new Error('Insufficient time remaining');
}

// For long operations, check periodically
for (const item of items) {
if (context.getRemainingTimeInMillis() < 10000) {
// Save progress and exit gracefully
await saveProgress(processedItems);
throw new Error('Timeout approaching, saved progress');
}
await processItem(item);
}
};

Set downstream timeouts

javascript
const axios = require('axios');

// Always set timeouts on HTTP calls
const response = await axios.get('https://api.example.com/data', {
timeout: 5000 // 5 seconds
});

Out of Memory (OOM) Crash

Severity: HIGH

Situation: Lambda function processing data

Symptoms:
Function stops abruptly without error.
CloudWatch logs appear truncated.
"Max Memory Used" hits configured limit.
Inconsistent behavior under load.

Why this breaks:
When Lambda exceeds memory allocation, AWS forcibly terminates
the runtime. This happens without raising a catchable exception.

Common causes:

  • Processing large files in memory

  • Memory leaks across invocations

  • Buffering entire response bodies

  • Heavy libraries consuming too much memory

Recommended fix:

Increase memory allocation

yaml
Resources:
  MyFunction:
    Type: AWS::Serverless::Function
    Properties:
      MemorySize: 1024  # MB (128-10240)
      # More memory = more CPU too

Stream large data

javascript
// BAD - loads entire file into memory
const data = await s3.getObject(params).promise();
const content = data.Body.toString();

// GOOD - stream processing
const { S3Client, GetObjectCommand } = require('@aws-sdk/client-s3');
const s3 = new S3Client({});

const response = await s3.send(new GetObjectCommand(params));
const stream = response.Body;

// Process stream in chunks
for await (const chunk of stream) {
await processChunk(chunk);
}

Monitor memory usage

javascript
exports.handler = async (event, context) => {
  const used = process.memoryUsage();
  console.log('Memory:', {
    heapUsed: Math.round(used.heapUsed / 1024 / 1024) + 'MB',
    heapTotal: Math.round(used.heapTotal / 1024 / 1024) + 'MB'
  });
  // ...
};

Use Lambda Power Tuning

bash
# Find optimal memory setting

https://github.com/alexcasalboni/aws-lambda-power-tuning

VPC-Attached Lambda Cold Start Delay

Severity: MEDIUM

Situation: Lambda functions in VPC accessing private resources

Symptoms:
Extremely slow cold starts (was 10+ seconds, now ~100ms).
Timeouts on first invocation after idle period.
Functions work in VPC but slow compared to non-VPC.

Why this breaks:
Lambda functions in VPC need Elastic Network Interfaces (ENIs).
AWS improved this significantly with Hyperplane ENIs, but:

  • First cold start in VPC still has overhead
  • NAT Gateway issues can cause timeouts
  • Security group misconfig blocks traffic
  • DNS resolution can be slow

Recommended fix:

Verify VPC configuration

yaml
Resources:
  MyFunction:
    Type: AWS::Serverless::Function
    Properties:
      VpcConfig:
        SecurityGroupIds:
          - !Ref LambdaSecurityGroup
        SubnetIds:
          - !Ref PrivateSubnet1
          - !Ref PrivateSubnet2  # Multiple AZs

LambdaSecurityGroup:
Type: AWS::EC2::SecurityGroup
Properties:
GroupDescription: Lambda SG
VpcId: !Ref VPC
SecurityGroupEgress:
- IpProtocol: tcp
FromPort: 443
ToPort: 443
CidrIp: 0.0.0.0/0 # Allow HTTPS outbound

Use VPC endpoints for AWS services

yaml
# Avoid NAT Gateway for AWS service calls
DynamoDBEndpoint:
  Type: AWS::EC2::VPCEndpoint
  Properties:
    ServiceName: !Sub com.amazonaws.${AWS::Region}.dynamodb
    VpcId: !Ref VPC
    RouteTableIds:
      - !Ref PrivateRouteTable
    VpcEndpointType: Gateway

S3Endpoint:
Type: AWS::EC2::VPCEndpoint
Properties:
ServiceName: !Sub com.amazonaws.${AWS::Region}.s3
VpcId: !Ref VPC
VpcEndpointType: Gateway

Only use VPC when necessary

Don't attach Lambda to VPC unless you need:

  • Access to RDS/ElastiCache in VPC

  • Access to private EC2 instances

  • Compliance requirements

Most AWS services can be accessed without VPC.

Node.js Event Loop Not Cleared

Severity: MEDIUM

Situation: Node.js Lambda function with callbacks or timers

Symptoms:
Function takes full timeout duration to return.
"Task timed out" even though logic completed.
Extra billing for idle time.

Why this breaks:
By default, Lambda waits for the Node.js event loop to be empty
before returning. If you have:

  • Unresolved setTimeout/setInterval

  • Dangling database connections

  • Pending callbacks

Lambda waits until timeout, even if your response was ready.

Recommended fix:

Tell Lambda not to wait for event loop

javascript
exports.handler = async (event, context) => {
  // Don't wait for event loop to clear
  context.callbackWaitsForEmptyEventLoop = false;

// Your code here
const result = await processRequest(event);

return {
statusCode: 200,
body: JSON.stringify(result)
};
};

Close connections properly

javascript
// For database connections, use connection pooling
// or close connections explicitly

const mysql = require('mysql2/promise');

exports.handler = async (event, context) => {
context.callbackWaitsForEmptyEventLoop = false;

const connection = await mysql.createConnection({...});
try {
const [rows] = await connection.query('SELECT * FROM users');
return { statusCode: 200, body: JSON.stringify(rows) };
} finally {
await connection.end(); // Always close
}
};

API Gateway Payload Size Limits

Severity: MEDIUM

Situation: Returning large responses or receiving large requests

Symptoms:
"413 Request Entity Too Large" error
"Execution failed due to configuration error: Malformed Lambda proxy response"
Response truncated or failed

Why this breaks:
API Gateway has hard payload limits:

  • REST API: 10 MB request/response

  • HTTP API: 10 MB request/response

  • Lambda itself: 6 MB sync response, 256 KB async

Exceeding these causes failures that may not be obvious.

Recommended fix:

For large file uploads

javascript
// Use presigned S3 URLs instead of passing through API Gateway

const { S3Client, PutObjectCommand } = require('@aws-sdk/client-s3');
const { getSignedUrl } = require('@aws-sdk/s3-request-presigner');

exports.handler = async (event) => {
const s3 = new S3Client({});

const command = new PutObjectCommand({
Bucket: process.env.BUCKET_NAME,
Key: uploads/${Date.now()}.file
});

const uploadUrl = await getSignedUrl(s3, command, { expiresIn: 300 });

return {
statusCode: 200,
body: JSON.stringify({ uploadUrl })
};
};

For large responses

javascript
// Store in S3, return presigned download URL
exports.handler = async (event) => {
  const largeData = await generateLargeReport();

await s3.send(new PutObjectCommand({
Bucket: process.env.BUCKET_NAME,
Key: reports/${reportId}.json,
Body: JSON.stringify(largeData)
}));

const downloadUrl = await getSignedUrl(s3,
new GetObjectCommand({
Bucket: process.env.BUCKET_NAME,
Key: reports/${reportId}.json
}),
{ expiresIn: 3600 }
);

return {
statusCode: 200,
body: JSON.stringify({ downloadUrl })
};
};

Infinite Loop or Recursive Invocation

Severity: HIGH

Situation: Lambda triggered by events

Symptoms:
Runaway costs.
Thousands of invocations in minutes.
CloudWatch logs show repeated invocations.
Lambda writing to source bucket/table that triggers it.

Why this breaks:
Lambda can accidentally trigger itself:

  • S3 trigger writes back to same bucket

  • DynamoDB trigger updates same table

  • SNS publishes to topic that triggers it

  • Step Functions with wrong error handling

Recommended fix:

Use different buckets/prefixes

yaml
# S3 trigger with prefix filter
Events:
  S3Event:
    Type: S3
    Properties:
      Bucket: !Ref InputBucket
      Events: s3:ObjectCreated:*
      Filter:
        S3Key:
          Rules:
            - Name: prefix
              Value: uploads/  # Only trigger on uploads/

Output to different bucket or prefix

OutputBucket or processed/ prefix

Add idempotency checks

javascript
exports.handler = async (event) => {
  for (const record of event.Records) {
    const key = record.s3.object.key;

// Skip if this is a processed file
if (key.startsWith('processed/')) {
console.log('Skipping already processed file:', key);
continue;
}

// Process and write to different location
await processFile(key);
await writeToS3(processed/${key}, result);
}
};

Set reserved concurrency as circuit breaker

yaml
Resources:
  RiskyFunction:
    Type: AWS::Serverless::Function
    Properties:
      ReservedConcurrentExecutions: 10  # Max 10 parallel
      # Limits blast radius of runaway invocations

Monitor with CloudWatch alarms

yaml
InvocationAlarm:
  Type: AWS::CloudWatch::Alarm
  Properties:
    MetricName: Invocations
    Namespace: AWS/Lambda
    Statistic: Sum
    Period: 60
    EvaluationPeriods: 1
    Threshold: 1000  # Alert if >1000 invocations/min
    ComparisonOperator: GreaterThanThreshold

Validation Checks

Hardcoded AWS Credentials

Severity: ERROR

AWS credentials must never be hardcoded

Message: Hardcoded AWS access key detected. Use IAM roles or environment variables.

AWS Secret Key in Source Code

Severity: ERROR

Secret keys should use Secrets Manager or environment variables

Message: Hardcoded AWS secret key. Use IAM roles or Secrets Manager.

Overly Permissive IAM Policy

Severity: WARNING

Avoid wildcard permissions in Lambda IAM roles

Message: Overly permissive IAM policy. Use least privilege principle.

Lambda Handler Without Error Handling

Severity: WARNING

Lambda handlers should have try/catch for graceful errors

Message: Lambda handler without error handling. Add try/catch.

Missing callbackWaitsForEmptyEventLoop

Severity: INFO

Node.js handlers should set callbackWaitsForEmptyEventLoop

Message: Consider setting context.callbackWaitsForEmptyEventLoop = false

Default Memory Configuration

Severity: INFO

Default 128MB may be too low for many workloads

Message: Using default 128MB memory. Consider increasing for better performance.

Low Timeout Configuration

Severity: WARNING

Very low timeout may cause unexpected failures

Message: Timeout of 1-3 seconds may be too low. Increase if making external calls.

No Dead Letter Queue Configuration

Severity: WARNING

Async functions should have DLQ for failed invocations

Message: No DLQ configured. Add for async invocations.

Importing Full AWS SDK v2

Severity: WARNING

Import specific clients from AWS SDK v3 for smaller packages

Message: Importing full AWS SDK. Use modular SDK v3 imports for smaller packages.

Hardcoded DynamoDB Table Name

Severity: WARNING

Table names should come from environment variables

Message: Hardcoded table name. Use environment variable for portability.

Collaboration

Delegation Triggers

  • user needs GCP serverless -> gcp-cloud-run (Cloud Run for containers, Cloud Functions for events)
  • user needs Azure serverless -> azure-functions (Azure Functions, Logic Apps)
  • user needs database design -> postgres-wizard (RDS design, or use DynamoDB patterns)
  • user needs authentication -> auth-specialist (Cognito, API Gateway authorizers)
  • user needs complex workflows -> workflow-automation (Step Functions, EventBridge)
  • user needs AI integration -> llm-architect (Lambda calling Bedrock or external LLMs)

When to Use

Use this skill when the request clearly matches the capabilities and patterns described above.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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