AWS Serverless

AWS Serverless

Purpose

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.

This skill provides operational guidance for AWS Serverless, including tool usage patterns, workflows, and quality expectations aligned with Syncolab skill standards.

When to Use

• Use when the user needs help with AWS Serverless.
• When integrations for this domain are available and the task matches the workflows below.

When NOT to Use

• When the task is unrelated to AWS Serverless or covered by a more specific skill.
• When required integrations or credentials are unavailable.

Expected Outcome

• Correct use of domain tools with verified results (not fabricated).
• Clear summary of actions taken, data returned, and recommended next steps.
• Errors and missing permissions reported explicitly.

Inputs to Gather

• User goal, constraints, and any identifiers (URLs, IDs, project keys).
• Available tool sets and connection status.
• Relevant context from related systems before destructive writes.

Workflow

1. Confirm the request maps to AWS Serverless and required tools are available.
2. Gather identifiers and scope (project, channel, repo, date range, etc.).
3. Follow the domain guidance below; prefer list/search before get/update when applicable.
4. Execute tool calls using schemas from the integration; never invent tool output.
5. Summarize results and offer logical follow-ups.

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 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']

```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"

// 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

// 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

Tool Availability Rules

Related tool sets

• custom-apis

Review / Decision / Execution Criteria

• Prefer smallest safe change; confirm destructive actions with the user.
• Use evidence from tool responses; cite IDs and links when present.
• Match integration-specific conventions (JQL, RFC3339, A1 notation, etc.).

Output Format

Report:

1. What was requested and what was done.
2. Key results (tables or bullets).
3. Errors, blockers, or missing permissions.
4. Suggested next steps.

Quality Bar

• Specific, actionable, and grounded in tool output.
• Concise unless the user asked for detail.
• Respect rate limits, pagination, and API semantics.

Safety and Boundaries

• Do not commit secrets, tokens, or PII into skills or user-visible logs.
• Do not fabricate validation, send, or write confirmations.
• Confirm destructive operations (delete, destroy, mass update) when appropriate.

Escalation / Dispatch Rules

• If the task spans multiple domains, use or suggest related skills via relationships.skills.
• If write access is required but unavailable, dispatch or ask the user to enable tools.

References

• Legacy content migrated from skills/old_skills.json (aws-serverless).
• skills/skill.instruction.md, skills/meta.instructions.md