Guided tour

1. 💡01

   GPS-Powered Order Orchestration Platform

   Arrive is a capacity-aware order orchestration platform that ensures food is freshly prepared as customers approach the restaurant. It leverages geofencing and real-time kitchen capacity evaluation to optimize order dispatching.

   • !Uses GPS for order orchestration
   • ✓Employs geofencing technology
2. 🛠02

   Microservice Architecture

   The project is structured as a layered microservice architecture, utilizing AWS Lambda for backend services and DynamoDB for data storage. Each service, such as orders and users, operates independently while sharing utilities through a Lambda Layer.

   • ✓Utilizes AWS Lambda for backend services
   • ✓Follows a microservice architecture
3. 📄03

   README.md: Project Overview

   The README.md provides a comprehensive overview of the Arrive platform, detailing its purpose, features, and architecture. This file reflects the developer's emphasis on clear documentation and user guidance.

   • !Contains project overview and architecture
   • ✓Provides detailed testing structure

   README.md

   # Arrive Platform
   
   > GPS-Powered Just-in-Time Kitchen Orchestration
   
   **Built with ❤️ via AI pair programming.**
   
   ---
   
   ## 🧭 Overview
   
   Arrive is a capacity-aware order orchestration platform. It flips the traditional takeout and curbside model on its head by delaying kitchen dispatch until the customer is physically approaching the restaurant, ensuring food is always freshly prepared exactly when they arrive.

4. ✓04

   Well-Tested Codebase

   The project employs a variety of testing frameworks, including pytest for Python and Jest for JavaScript/TypeScript. Tests are organized in dedicated directories for each service and include unit and integration tests.

   • ✓Includes unit and integration tests
   • !Uses pytest for Python testing
5. 🚀05

   CI/CD Workflows for Deployment

   The project includes CI/CD workflows defined in GitHub Actions, facilitating automated testing and deployment. The deployment target is not explicitly stated but is managed through scripts and AWS services.

   • ✓Configured CI/CD workflows
   • ✓Automated testing in CI
6. ▶06

   Clone the Repository

   To explore the project, you can clone the repository using the command below. There is no live demo available at this time.

   • !Repository available for cloning

   git clone https://github.com/shashankcm95/AADI

graph TD
    subgraph Clients
      C[Customer App<br/>React Native / iOS]
      A[Admin Portal<br/>React]
      W[Customer Web<br/>React]
    end

    subgraph AWS Cloud
      API[API Gateway]
      COG[Cognito Auth]
      
      subgraph Microservices
        O[Orders Service<br/>Python Lambda]
        U[Users Service<br/>Python Lambda]
        R[Restaurants Service<br/>Python Lambda]
        POS[POS Integration<br/>Python Lambda]
        S[Shared Layer<br/>Utilities]
      end
      
      subgraph Data Stores
        DDB[(DynamoDB Tables)]
      end
      
      subgraph Location Services
        LOC[AWS Location Service<br/>Geofencing]
        EB[EventBridge]
      end
    end
    
    C -->|Trigger Geofence| LOC
    LOC -->|Event| EB
    EB -->|Dispatch El