Serverless Application Model (SAM)¶

Overview¶

The AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications. It extends AWS CloudFormation to provide a simplified way to define serverless applications. It provides shorthand syntax to express functions, APIs, databases, and event source mappings. With just a few lines per resource, you can define the application you want and model it using YAML.

SAM supports the following resource types:

AWS::Serverless::Api
AWS::Serverless::Application
AWS::Serverless::Function
AWS::Serverless::HttpApi
AWS::Serverless::LayerVersion
AWS::Serverless::SimpleTable
AWS::Serverless::StateMachine

Key Components¶

1. SAM Template Structure¶

AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: SAM Template Example

Resources:
  MyFunction:
    Type: AWS::Serverless::Function
    Properties:
      Handler: index.handler
      Runtime: nodejs14.x
      CodeUri: ./src/

2. Main Resource Types¶

AWS::Serverless::Function¶

MyFunction:
  Type: AWS::Serverless::Function
  Properties:
    Handler: app.handler
    Runtime: python3.9
    CodeUri: ./
    MemorySize: 128
    Timeout: 3
    Environment:
      Variables:
        TABLE_NAME: !Ref MyTable
    Events:
      ApiEvent:
        Type: Api
        Properties:
          Path: /hello
          Method: get

AWS::Serverless::Api¶

MyApi:
  Type: AWS::Serverless::Api
  Properties:
    StageName: prod
    Cors:
      AllowMethods: "'GET,POST,OPTIONS'"
      AllowHeaders: "'content-type'"
      AllowOrigin: "'*'"

AWS::Serverless::LayerVersion¶

MyLayer:
  Type: AWS::Serverless::LayerVersion
  Properties:
    LayerName: my-layer
    Description: My layer description
    ContentUri: ./layer/
    CompatibleRuntimes:
      - python3.9

Common Commands¶

Installation¶

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

# Verify installation
sam --version

Project Management¶

# Create new project
sam init

# Build project
sam build

# Deploy application
sam deploy --guided

# Local testing
sam local start-api
sam local invoke "FunctionName"

# Package application
sam package \
  --template-file template.yaml \
  --output-template-file packaged.yaml \
  --s3-bucket my-bucket

Local Development¶

Local API Testing¶

# Start local API
sam local start-api

# Invoke single function
sam local invoke -e events/event.json

# Generate sample event
sam local generate-event apigateway aws-proxy

Environment Variables¶

Resources:
  MyFunction:
    Type: AWS::Serverless::Function
    Properties:
      Environment:
        Variables:
          DB_NAME: my-database
          API_KEY: !Ref ApiKey

Event Source Mappings¶

API Gateway¶

Events:
  ApiEvent:
    Type: Api
    Properties:
      Path: /hello
      Method: get

S3 Events¶

Events:
  S3Event:
    Type: S3
    Properties:
      Bucket: !Ref MyBucket
      Events: s3:ObjectCreated:*

DynamoDB Events¶

Events:
  StreamEvent:
    Type: DynamoDB
    Properties:
      Stream: !GetAtt MyTable.StreamArn
      StartingPosition: LATEST
      BatchSize: 100

Best Practices¶

1. Security¶

Use IAM roles with least privilege
Enable X-Ray for tracing
Implement proper error handling
Use Secrets Manager for sensitive data

2. Performance¶

Optimize function memory allocation
Use layers for common dependencies
Implement caching where appropriate
Consider cold start impact

3. Monitoring¶

MyFunction:
  Type: AWS::Serverless::Function
  Properties:
    Tracing: Active
    AutoPublishAlias: live
    DeploymentPreference:
      Type: Canary10Percent5Minutes

4. Cost Optimization¶

Use appropriate memory settings
Implement proper timeouts
Use provisioned concurrency when needed
Monitor and adjust based on usage

Testing and Debugging¶

Unit Testing¶

# Example test using pytest
def test_handler():
    response = app.handler(event, context)
    assert response['statusCode'] == 200

SAM Local Debugging¶

# Debug with VS Code
sam local invoke -d 5858 MyFunction

# Generate sample events
sam local generate-event s3 put

CI/CD Integration¶

GitHub Actions Example¶

name: SAM Deploy
on: [push]
jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - uses: aws-actions/setup-sam@v1
      - uses: aws-actions/configure-aws-credentials@v1
      - run: sam build
      - run: sam deploy --no-confirm-changeset

AWS CodePipeline Integration¶

Pipeline:
  Type: AWS::CodePipeline::Pipeline
  Properties:
    Stages:
      - Name: Source
        Actions:
          - Name: Source
            ActionTypeId:
              Category: Source
              Provider: GitHub
      - Name: Build
        Actions:
          - Name: Build
            ActionTypeId:
              Category: Build
              Provider: CodeBuild

Troubleshooting¶

Common Issues¶

Deployment Failures
Check IAM permissions
Verify S3 bucket accessibility
Review CloudFormation errors
Function Execution Issues
Check CloudWatch Logs
Verify environment variables
Test locally with SAM CLI
API Gateway Issues
Verify CORS settings
Check API Gateway logs
Test endpoints locally

Advanced Features¶

Custom Runtime¶

MyFunction:
  Type: AWS::Serverless::Function
  Properties:
    Runtime: provided
    Handler: bootstrap
    CodeUri: ./custom-runtime/

VPC Configuration¶

MyFunction:
  Type: AWS::Serverless::Function
  Properties:
    VpcConfig:
      SecurityGroupIds:
        - sg-123456
      SubnetIds:
        - subnet-123456

Step Functions Integration¶

StateMachine:
  Type: AWS::Serverless::StateMachine
  Properties:
    DefinitionUri: statemachine/definition.asl.json
    Policies:
      - LambdaInvokePolicy:
          FunctionName: !Ref MyFunction

Production Considerations¶

1. Deployment Strategies¶

Use staged deployments
Implement rollback mechanisms
Consider traffic shifting
Use aliases for version management

2. Monitoring and Alerting¶

Set up CloudWatch Alarms
Configure X-Ray tracing
Implement custom metrics
Set up logging standards

3. Scaling and Performance¶

Configure concurrency limits
Use provisioned concurrency
Implement caching strategies
Optimize cold starts