Functional & Non-Functional Requirements

Requirements

To design the online ticketing platform, we need to outline both functional and non-functional requirements. Functional requirements include:

• Ability to browse events (movies, concerts, sports)
• User account management (registration, login, profile management)
• Search and filter capabilities for events
• Dynamic seating selection with graphical interface
• Payment processing and order confirmation
• Ticket delivery options (e-ticket, physical ticket, mobile ticket)

Non-functional requirements encompass:

• Scalability to handle peak loads (e.g., during popular event launches)
• High availability and disaster recovery strategies
• Performance: Page loading times under 2 seconds
• Security measures to protect sensitive user data
• Compliance with industry regulations (e.g., PCI DSS for payments)

Capacity Estimation

Estimation

The development of the ticketing platform can be broken down into several phases, estimating both time and resources required.

• Phase 1: Research and Planning - 2 weeks to gather requirements and finalize technology stack.
• Phase 2: Design - 3 weeks for system architecture, database schema design, and UI/UX mockups.
• Phase 3: Development - 12 weeks for building the frontend and backend, integrating payment gateways, and implementing security measures.
• Phase 4: Testing - 4 weeks for unit tests, integration tests, and user acceptance testing.
• Overall, the estimated timeline is approximately 21 weeks. Resources needed include 1 project manager, 2 frontend developers, 2 backend developers, 1 QA engineer, and 1 designer.

API Design

API Design

RESTful APIs enable communication between the frontend and backend. Key endpoints might include:

• GET /events - Retrieve a list of events, supporting query parameters for filtering and sorting.
• GET /events/{id} - Get details for a specific event including available seats.
• POST /users - Create a new user account.
• POST /login - Authenticate a user.
• POST /orders - Create a new ticket order.
• GET /orders/{userId} - Retrieve orders for a specific user.

Response formats should be standardized, returning JSON data with appropriate HTTP status codes.

Database Design

Database Design

A relational database, such as PostgreSQL, will support the main data requirements. Key tables include:

• Users - Stores user information (username, password hash, email, etc).
• Events - Contains event details (name, date, location, pricing).
• Orders - Links users to their purchased tickets (userId, eventId, ticketIds).
• Tickets - Stores individual ticket information (seat number, status, eventId).

This design allows for relational integrity and efficient querying, ensuring quick access to data associated with events, users, and orders.

High Level Design

High-Level Architecture

The architecture of the system can be represented as follows:

• Client - User interface for ticket browsing and purchase.
• Load Balancer - Distributes incoming traffic among backend services.
• Web Server - Hosts our API services (Node.js, Spring Boot).
• Database - Relational database for persistent storage.
• Cache - Redis/Memcached for frequently accessed data (event lists, user sessions).
• Queue - Message broker (RabbitMQ) for processing asynchronous tasks (order updates, notifications).

This architecture emphasizes scalability and fault tolerance, allowing for efficient load handling.

Request Flows

Request Flow

The typical request flow for a ticket purchase is as follows:

1. User requests event details via the web interface.
2. The request is routed through the load balancer to a web server.
3. The web server queries the database for event data and returns it to the client.
4. User selects seats and initiates the purchase.
5. The web server processes the payment and creates an order in the database.
6. An asynchronous message is sent to the queue for ticket confirmation.

This flow ensures a smooth user experience and decouples payment processing from the main user flow.

Detailed Component Design

Key Components

The main components of the ticketing system include:

• User Management Service - Handles account creation, login, and authentication.
• Event Management Service - Manages event data, including creation and updates.
• Order Management Service - Processes ticket orders and interacts with payment gateways.
• Notification Service - Sends confirmation emails and SMS to users post-purchase.
• Analytics Service - Gathers user behavior and sale data for reporting.

These components can be developed independently and scaled based on demand.

Trade-offs & Tech Choices

Trade-Offs

When designing the system, certain trade-offs must be considered:

• Consistency vs Availability - In a situation with high user demand, we may prioritize availability by allowing eventual consistency in ticket inventory updates, which may lead to overselling.
• Complexity vs Flexibility - Implementing microservices can provide flexibility but adds complexity in terms of deployment, monitoring, and inter-service communication.
• Cost vs Performance - Using managed cloud services can enhance performance but may increase operational costs. We must balance service level needs with the budget.

Failure Scenarios & Bottlenecks

Failure Scenarios

In any system, potential failure scenarios must be planned for:

• Database Failure - Implement replication and failover strategies to ensure data availability.
• Payment Gateway Failure - Establish fallback mechanisms for users to preserve their transactions without losing data.
• Server Downtime - Employ load balancers and multiple instances of services to ensure high availability.
• Network Latency - Use caching strategies to speed up frequent reads and minimize slowdown in response times.

Future Improvements

Future Improvements

To keep the platform relevant and competitive, several improvements can be considered:

• Advanced Analytics - Integrate machine learning capabilities to provide personalized event recommendations for users.
• Mobile App Development - Expanding to mobile platforms could enhance user engagement and accessibility.
• Dynamic Pricing Models - Implement algorithms for pricing tickets based on demand patterns and seat sales history.
• Enhanced User Experience - Continuously gather user feedback to refine UI/UX and make the purchasing process seamless.

High Level Architecture Diagram

Database ER Diagram

Request Flow Sequence Diagram