Fleet Management Backend

Project Overview

The Fleet Management Backend is a system designed to manage a fleet of vehicles, providing functionalities such as vehicle registration, real-time tracking, maintenance records management, and usage analytics. This backend service is built with NestJS and other modern technologies, providing a scalable and robust platform for managing vehicle data and operations efficiently.

Features

• Vehicle Registration
• Vehicle Tracking
• Vehicle Maintenance Records
• Usage Analytics

Tech Stack

Core Technologies

• NestJS: A progressive Node.js framework for building efficient, reliable, and scalable server-side applications.
• MongoDB (Mongoose): A NoSQL database for storing vehicle data, maintenance records, and other information.
• BullMQ: A high-performance Node.js library for handling background jobs and message queues.
• Swagger: Used for API documentation and testing.

Development Tools

• TypeScript: A strongly typed programming language that builds on JavaScript, giving you better tooling at any scale.
• Jest: A delightful JavaScript testing framework with a focus on simplicity.
• ESLint: A tool for identifying and fixing problems in your JavaScript/TypeScript code.
• Prettier: An opinionated code formatter that enforces a consistent style.
• Supertest: A library for testing HTTP servers.

Architecture

Overview

The Fleet Management Backend follows a modular architecture using NestJS. It is organized into several key modules that separate concerns and make the codebase easy to maintain and scale. Here's a high-level overview of the architecture:

1. Modules: Each feature (e.g., vehicle registration, tracking, maintenance) is encapsulated in its own module.
2. Controllers: Responsible for handling incoming requests and returning responses to the client.
3. Services: Implement business logic and interact with repositories for data access.
4. Repositories: Handle data access and persistence using Mongoose for MongoDB.
5. Queues: Used for handling asynchronous tasks and background processing with BullMQ.

Key Components

• Vehicle Module: Manages vehicle registration and maintenance logs. Interfaces with the MongoDB database via Mongoose to persist vehicle data.

• Tracking Module: Provides real-time tracking of vehicle status and location. It also processes tracking data from simulated IoT devices. This module simulates data for demonstration purposes.

• Queue Module: This module is used to process IoT device data which is simulated using ./.scritps/iot-simulator.ts

Directory Structure

.
└── fleet-backend/
    ├── .scripts
    ├── src/
    │   └── modules/
    │       ├── queues/
    │       │   └── consumers
    │       ├── vehicle/
    │       │   ├── dtos
    │       │   └── models
    │       └── tracking/
    │           ├── dtos
    │           └── models
    └── test

Getting Started

Prerequisites

Ensure you have the following installed:

• Node.js
• yarn
• Docker

Installation

1. Clone the repository:

   git clone git@github.com:jskod/fleet-backend.git
   cd fleet-backend

2. Install dependencies:

   yarn install

3. Set up environment variables:

   For this demo .env was committed to make it easy for testing purposes. Otherwise, '.env' should never be added to source control.

4. Start the development server using Docker Compose:

   docker-compose up --build

5. Simulate IoT Device Data:

   yarn run simulate:iot

Database Seeding

For this demo, database seeding is performed at the time of Docker container creation. .scripts/seed-db.js is used to seed 10 vehicles that will also be used for IoT Data simulation script .scripts/iot-simulator.ts.

Unit Tests

To run unit tests, just run following command:

yarn run test

Screenshot of all tests passing:

Unit Test Coverage

To run unit tests and see coverage report, run following command:

yarn run test:cov

Screenshot of coverage report: 100% unit test coverage.

E2E Tests

To run e2e test, we need to have all required components such as redis and mongodb database. If we don't have locally installed components; we can use docker to run the test for the sake of testing for this demo. Please note that for the sake of this assignment I only wrote e2e test for Vehicle Controller which should be good enough for assessment.

Follow the steps:

1. Run docker-compose using command docker-compose up.
2. Now find running docker container docker ps.
3. In our case container name is fleet_backend and we can start bash using command docker exec -it fleet_backend /bin/sh
4. Now once you are inside container's bash shell, run command npm run test:e2e. (we use npm here as we don't have yarn installed by default)

API Documentation

The API documentation is generated using Swagger. Once the application is running, access the documentation at:

http://localhost:3000/docs