2. AWS SAM — Serverless Application Model

AWS Serverless Application Model (SAM) is an open-source framework that simplifies building, testing, and deploying serverless applications on AWS. Built on top of AWS CloudFormation, SAM provides shorthand syntax specifically designed for serverless resources like Lambda functions, APIs, event mappings, and permissions.

Prerequisites

Before diving into AWS SAM, ensure you have the following installed and configured:

• AWS CLI v2 configured with appropriate credentials
• Docker Desktop (required for local Lambda testing)
• Node.js 18+ or Python 3.9+ (depending on your runtime)
• AWS SAM CLI (installed via brew install aws-sam-cli or pip)

sam --version
# Expected output: SAM CLI, version 1.105.0
aws --version

Initializing a Project

Start by scaffolding a new SAM project. The CLI provides several templates out of the box:

sam init --runtime nodejs18.x --name aevum-serverless-api --app-template hello-world

This creates a standardized directory structure:

aevum-serverless-api/
├── .aws-sam/
├── events/
│   └── event.json
├── hello_world/
│   ├── app.py
│   └── requirements.txt
├── samconfig.toml
├── template.yaml
└── tests/
    └── unit/
        └── test_handler.py

Understanding the Template

The template.yaml file is the heart of your SAM application. It defines resources, events, and permissions using simplified syntax:

AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: Aevum API Gateway + Lambda example

Resources:
  GetDataFunction:
    Type: AWS::Serverless::Function
    Properties:
      Runtime: python3.9
      Handler: app.lambda_handler
      CodeUri: hello_world/
      Events:
        ApiEvent:
          Type: Api
          Properties:
            Path: /data/{id}
            Method: get
      Policies:
        - DynamoDBReadPolicy:
            TableName: !Ref DataStore

  DataStore:
    Type: AWS::Serverless::SimpleTable
    Properties:
      PrimaryKey:
        Name: id
        Type: String

Building & Testing Locally

SAM leverages Docker to emulate the Lambda execution environment locally. This ensures near-identical behavior to production:

# Build dependencies into container images
sam build

# Start local API Gateway emulator
sam local start-api

# Test endpoint
curl http://localhost:3000/data/test123

The local emulator supports API Gateway v1 & v2, event mapping, and VPC networking simulation. Use --warm-containers EAGER to avoid cold start delays during rapid iteration.

Deploying to AWS

Once validated, deploy your application with the guided CLI command. It automatically creates or updates a CloudFormation stack, provisions IAM roles, and outputs your endpoint URLs:

sam deploy --guided

Best Practices

• Use Policies shorthand: SAM's policy templates reduce IAM misconfigurations by following least-privilege defaults.
• Enable X-Ray tracing: Add Tracing: Active to functions for distributed tracing without boilerplate.
• Pin runtime versions: Avoid latest tags in production. Use python3.11, nodejs20.x, etc.
• Separate environments: Use samconfig.toml profiles for dev, staging, and production deployments.
• Leverage layers: Package shared dependencies in Lambda Layers to reduce deployment package size and cold start times.

Next Steps

Now that you understand the core workflow of AWS SAM, proceed to the next module to learn how to containerize your functions and run advanced local simulations with Docker networking and VPC emulation.