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 restaurants. It leverages geofencing and real-time kitchen capacity evaluation to optimize dispatch timing.

   • ✓Uses geofencing for order management
   • ✓Built with React and Python
   • ✓Supports just-in-time dispatch
2. 🛠02

   Microservice Architecture

   The project employs a layered microservice architecture using AWS Lambda for backend services, with separate services for orders, users, and restaurants. Shared utilities are deployed as a Lambda Layer to streamline functionality.

   • ✓Utilizes AWS Lambda for backend
   • ✓Follows microservice design pattern
   • !Has a layered architecture
3. 📄03

   Key Utility: Geofencing Logic

   The file `services/orders/tests/test_geofence_events.py` contains tests for geofence event handling, showcasing the developer's focus on ensuring accurate location-based order management. This reflects a commitment to reliable service delivery.

   • !Contains tests for geofence logic
   • ✓Focus on testing for critical features

   services/orders/tests/test_geofence_events.py

   import pytest
   
   @pytest.mark.parametrize('location, expected_event', [
       ("nearby", "dispatch_event"),
       ("far_away", "no_event")
   ])
   def test_geofence_events(location, expected_event):
       assert geofence_handler(location) == expected_event
   

4. ✓04

   Well-Tested Codebase

   The project employs a comprehensive testing strategy with tests located in various services, including unit and integration tests. It uses pytest for Python tests and includes React testing with Jest.

   • !Tests with pytest for Python
   • ✓Includes React testing with Jest
   • ✓CI workflow for testing
5. 🚀05

   CI/CD Workflows for Deployment

   The project includes CI/CD workflows defined in GitHub Actions, facilitating automated testing and deployment processes. It targets AWS for deployment, leveraging services like API Gateway and Lambda.

   • ✓CI/CD workflows configured
   • ✓Uses AWS for deployment
   • ✓Automated deployment scripts present
6. ▶06

   Try It Out

   To explore the project further, you can clone the repository from GitHub. This will give you access to the full codebase and documentation.

   • !Clone the repository available

   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