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Connected Vehicles API

A boilerplate/starter project demonstrating serverless architecture using AWS services with local development capabilities. This project showcases the implementation of a simple API for managing connected vehicles data using modern serverless practices.

Architecture Overview

The project utilizes several AWS services:

  • API Gateway: HTTP API for RESTful endpoints
  • Lambda: Serverless compute for request handling
  • Step Functions: Orchestration of the validation and processing workflow
  • DynamoDB: NoSQL database for vehicle and user data

Key Features

  • Single-table design with composite keys (PK/SK) for DynamoDB
  • Asynchronous processing using Step Functions
  • Validation layer for data integrity
  • Local development environment
  • Python-based Lambda functions with PynamoDB ORM
  • Serverless Framework for infrastructure as code

Prerequisites

  • Node.js (v14 or later)
  • Python 3.9
  • AWS CLI configured for deployment
  • Serverless Framework CLI
  • Docker (for local DynamoDB)

Project Structure

connected-vehicles-api/
├── serverless.yml              # Serverless Framework configuration
├── requirements.txt            # Python production dependencies
├── requirements-dev.txt        # Python development dependencies
├── src/
│   ├── handlers/              # Lambda function handlers
│   ├── models/                # PynamoDB models
│   ├── services/              # Business logic services
│   └── utils/                 # Utility functions
├── tests/                     # Test files
└── seeds/                     # DynamoDB seed data

Getting Started

  1. Clone the repository:
git clone <repository-url>
cd connected-vehicles-api
  1. Install dependencies:
# Install Node.js dependencies
npm install

# Create and activate Python virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .\.venv\Scripts\activate

# Install Python dependencies
pip install -r requirements-dev.txt
  1. Start local development environment:
npm run start:local

Local Development

The project uses serverless-offline plugin for local development, which provides:

  • Local API Gateway emulation
  • Local Lambda function execution
  • Local DynamoDB instance
  • Hot reloading for development

Running Locally

Start the local development environment:

npm run start:local

This will start:

Testing the API

Create a vehicle:

curl -X POST http://localhost:4000/vehicles \
-H "Content-Type: application/json" \
-d '{
  "vehicle_id": "WDDJK7DA4FF954840",
  "torque": "308",
  "drivetrain": "4WD",
  "engine": "gasoline",
  "horsepower": "406"
}'

Add a vehicle feature:

curl -X POST http://localhost:4000/vehicles/WDDJK7DA4FF954840/features \
-H "Content-Type: application/json" \
-d '{
  "feature_type": "cameras",
  "feature_data": {
    "cameras": {
      "front_camera_center": {
        "foo": "bar"
      }
    },
    "recording_is_active": true
  }
}'

Testing

The project includes various types of tests:

  1. Run unit tests:
pytest tests/unit
  1. Run integration tests:
pytest tests/integration
  1. Run local API tests:
pytest tests/test_local_api.py

Deployment

Deploy to AWS:

# Deploy to development
npm run deploy:dev

# Deploy to production
npm run deploy:prod

DynamoDB Data Model

The project uses a single-table design with the following key schema:

  • Partition Key (PK): Entity identifier (e.g., "VIN#123", "ID#user1")
  • Sort Key (SK): Entity type or metadata (e.g., "#META#", "FEATURE#CAMERAS")

Example item:

{
  "PK": "VIN#WDDJK7DA4FF954840",
  "SK": "#META#",
  "vehicle_id": "WDDJK7DA4FF954840",
  "torque": "308",
  "drivetrain": "4WD",
  "engine": "gasoline",
  "horsepower": "406"
}

Future Enhancements

This is a starter project that can be extended with:

  • Authentication and authorization
  • Additional vehicle features
  • Real-time updates using WebSockets
  • Enhanced monitoring and logging
  • Additional data access patterns
  • CI/CD pipeline
  • Infrastructure testing

Contributing

This is a boilerplate project - feel free to use it as a starting point for your own implementation. Contributions to improve the base functionality are welcome.

License

MIT