The Online News Channel App is a modern and innovative platform for delivering news and information to users in real-time. This project is designed to provide a seamless experience for users to access the latest news, watch live streams, get personalized recommendations, and engage in discussions through comments.

• Features
• Technologies Used
• Directory Structure
• Getting Started
• Building and Running the Microservices
• API Endpoints
• User Interface
• Database
• Deployment
• Contributing
• License

• News Publishing: Allows administrators to publish news articles and updates in real-time.
• Content Aggregation: Aggregates news articles from various reliable sources.
• User Authentication: Provides user authentication and secure login functionality.
• User Comments: Enables users to post comments on news articles and engage in discussions.
• Live Streaming: Provides live streaming of news events and broadcasts.
• Recommendation: Offers personalized news recommendations based on user preferences.
• Notification: Sends push notifications to users for important news updates.
• AI and ML: Utilizes AI and ML technologies for content analysis and user behavior prediction.
• User Interface: Provides a user-friendly and responsive interface for both web and mobile platforms.
• Database: Stores user profiles, news articles, and other relevant information securely.

• Backend: Rust and Haskell
• Frontend: HTML, CSS, JavaScript
• Database: PostgreSQL for user profiles and MySQL for AI/ML generated info
• Containerization: Docker
• Orchestration: Kubernetes
• Continuous Integration/Deployment: GitLab CI/CD
• API Gateway: Nginx
• Reverse Proxy: Nginx
• Load Balancer: Nginx

Explain the directory structure and provide a brief description of each microservice and component.

Provide instructions on how to clone the repository, install dependencies, and set up the development environment.

Explain how to build and run each microservice using Docker and Kubernetes.

List the API endpoints for each microservice along with the required request parameters and expected responses.

Provide screenshots and brief explanations of the user interface for both web and mobile platforms.

Explain the database schema and the tables used for storing user profiles and AI/ML generated information.

Provide instructions on how to deploy the application to a production environment using Kubernetes and other tools.

Explain how other developers can contribute to the project and submit pull requests.

Specify the license under which the project is distributed (e.g., MIT License).

Provide contact information for inquiries and support.