Full Stack Applications - Rule Engine & Weather Monitor

This repository contains two full-stack applications: a Rule Engine and a Weather Monitoring system. Both applications are containerized using Docker for easy deployment and testing.

Deploy link :

• Rule Engine with AST: https://rule-engine-sand.vercel.app/
• Weather Monitor : https://weather-monitor-tau.vercel.app/

Table of Contents

Overview

• Full Stack Applications - Rule Engine & Weather Monitor
• Technology Stack
  • Rule Engine Application
  • Weather Monitor Application

Features

• Application Features
  • Rule Engine Application
    • Core Features
    • Query Optimization
    • Advanced Rule Combination Heuristics
  • Weather Monitoring Application
    • Core Features
    • Data Analysis
    • Advanced Features
    • Performance Optimization

Setup & Installation

• Getting Started
  • Option 1: Using Docker Compose
  • Option 2: Using Pre-built Docker Image

Technical Details

• Application Ports
  • Rule Engine
  • Weather Monitor

Main :

Technology Stack

Rule Engine Application

• Frontend: Next.js
• Backend: Golang (Gin Framework)
• Database: MongoDB

Weather Monitor Application

• Frontend: Next.js
• Backend: Golang (Gin Framework)
• Database: PostgreSQL (TimescaleDB)

Application Features

Rule Engine Application

Core Features:

• Rule Creation and Management
  • Create individual rules with multiple conditions
  • Combine 2+ rules with complex logical operations
  • Real-time rule evaluation based on input data

Query Optimization:

• Optimized queries for:
  • Rule creation
  • Rule combination
  • Rule evaluation
  • Rule optimization

Advanced Rule Combination Heuristics:

• Intelligent rule merging strategy:
  • Identifies and isolates common conditions for single evaluation
  • Preserves rule semantics during combination
  • Rules without common conditions: Combined using AND operations
  • Rules with common conditions: Merged using OR operations after extracting common conditions

Weather Monitoring Application

Core Features:

• Multi-City Weather Tracking
  • Real-time monitoring of three cities
  • Data collection every 5 minutes
  • Tracks:
    • Current temperature
    • "Feels like" temperature
    • Dominant weather condition

Data Analysis:

• Daily Data Aggregation and Rollups:
  • Maximum temperature
  • Minimum temperature
  • Average temperature
  • Per-city analysis

Advanced Features:

• Customizable Alert System
  • User-defined temperature thresholds for each city
  • Automated notification system
  • City-specific alert configurations

Performance Optimization:

• Query optimization using:
  • Database Views
  • TimescaleDB time_bucket function
  • Efficient data rollup strategies

Getting Started

There are two ways to run these applications:

Option 1: Using Docker Compose

1. Clone the repository:

git clone https://github.com/TejasThombare20/RuleEngine-WeatherMonitor.git
cd zeotap

2. Start all services using Docker Compose:

docker-compose up -d

3. Access the applications:
   • Rule Engine: http://localhost:3001
   • Weather Monitor: http://localhost:3002

Option 2: Using Pre-built Docker Image

1. Pull the image:

docker pull tejasthombare/zeotap

2. Run the container:

docker run -d \
  -p 3001:3000 \
  -p 3002:3000 \
  -p 8000:8000 \
  -p 9000:9000 \
  tejasthombare/zeotap

3. Access the applications:
   • Rule Engine Frontend: http://localhost:3001
   • Rule Engine Backend: http://localhost:8000
   • Weather Monitor Frontend: http://localhost:3002
   • Weather Monitor Backend: http://localhost:9000

Application Ports

Rule Engine

• Frontend: 3001
• Backend API: 8000

Weather Monitor

• Frontend: 3002
• Backend API: 9000

Project Structure

.
├── rule_engine/
│   ├── client/          # Next.js frontend
│   └── server/          # Golang backend
├── weather_monitoring/
│   ├── client/          # Next.js frontend
│   └── server/          # Golang backend
├── Dockerfile
├── docker-compose.yml
└── README.md