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🚀 AppHub

🌐 Live

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🧠 About

Job searching across multiple platforms quickly becomes chaotic. AppHub is a job search management tool that centralizes vacancies, applications, and tracking into a single structured workflow. The project was inspired by my own experience — I built it as a tool I actively use during my job search.


✨ Features

  • Secure authentication (JWT access & refresh tokens)
  • User profile management
  • Job aggregation and scraping from multiple sources
  • Structured transformation of raw job data into a normalized format
  • Job filtering and sorting based on relevance and user preferences
  • Application tracking system
    • Convert jobs into applications
    • Track status (applied, interview, rejected, etc.)
    • Add personal notes per application
  • Manual application creation for external platforms
  • Fully responsive UI for all devices

⚙️ Tech Stack

Frontend

  • React
  • TypeScript
  • Vite

Backend

  • Node.js
  • Express

Database

  • PostgreSQL

Background Processing

  • Bull (job queue)
  • Redis (caching + async jobs)

🏗 Architecture

  • REST API built with Express
  • Stateless authentication using JWT (access + refresh flow)
  • Job → Application lifecycle management
  • Async job processing pipeline (Bull + Redis + Worker)
  • PostgreSQL for persistent structured data
  • Redis for caching and queue handling
  • Worker service for background tasks (job parsing, processing)

🚀 Deployment

  • Vercel — frontend hosting
  • Railway — backend, PostgreSQL, Redis, and worker services
  • Docker — used for local development (Redis + worker setup)

🧪 Key Challenges

  • Designing a full-stack system from scratch (idea → architecture → implementation → deployment)
  • Structuring scalable data models for job → application lifecycle
  • Handling deployment differences between local and production environments (CORS, environment variables, API URLs)
  • Managing a multi-service architecture (frontend, backend, worker, database, queue)
  • Optimizing database queries for large datasets of scraped jobs
  • Building a reliable async processing pipeline using Bull + Redis

🔮 Future Improvements

  • Add unit and integration tests (auth, scraping, application flows)
  • Dockerize full production setup for easier deployment and consistency
  • Add analytics dashboard for job search progress and success tracking
  • Implement real-time notifications for application updates
  • Improve job matching and ranking algorithm
  • Add role-based access control (RBAC)

👨‍💻 Author

Stanislav Borychevskyi — Full Stack Developer
Focused on building scalable web applications, backend systems, and real-world problem-solving tools.

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