Meeting Room Booking System Design

Let's design a system to efficiently manage meeting room bookings for a large company.

1. Requirements

Functional Requirements:
- Room availability search based on time, date, and number of attendees.
- Booking a meeting room for a specific time slot.
- Recurring meeting support.
- Integration with employee calendars (e.g., Google Calendar, Outlook).
- Conflict detection and resolution.
- Reporting and analytics (e.g., room utilization).
- User authentication and authorization.
- Cancellation and modification of bookings.
Non-Functional Requirements:
- Scalability: Handle a large number of meeting rooms and employees.
- Concurrency: Multiple users should be able to book rooms simultaneously without conflicts.
- Reliability: The system should be reliable and available.
- Performance: Fast response times for search and booking operations.
- Security: Secure booking and access control.

2. High-Level Design

The system architecture will consist of the following components:

Web/Mobile Client: User interface for booking and managing meetings.
API Gateway: Entry point for all client requests. Handles authentication, authorization, and routing.
Booking Service: Core service responsible for managing meeting room bookings.
Room Service: Manages meeting room information (capacity, location, equipment).
User Service: Manages user information and authentication.
Calendar Integration Service: Integrates with external calendar systems (e.g., Google Calendar, Outlook).
Database: Stores data related to users, rooms, bookings, and availability.
Cache: Caches frequently accessed data to improve performance.
Message Queue: Asynchronously processes tasks such as calendar synchronization and reporting.

[High-Level Architecture Diagram]

Client --> API Gateway --> Booking Service <--> Room Service
API Gateway --> User Service
Booking Service --> Calendar Integration Service
Booking Service <--> Database <--> Cache
Booking Service --> Message Queue

3. Data Model

We'll use a relational database (e.g., PostgreSQL) to store the system data.

Users Table

Field	Type	Description
user_id	UUID	Unique identifier for the user
username	VARCHAR(255)	Username for login
email	VARCHAR(255)	Email address
password_hash	VARCHAR(255)	Hashed password
first_name	VARCHAR(255)	First name
last_name	VARCHAR(255)	Last name
calendar_id	VARCHAR(255)	Identifier for external calendar integration

Rooms Table

Field	Type	Description
room_id	UUID	Unique identifier for the room
room_name	VARCHAR(255)	Name of the room
capacity	INTEGER	Maximum number of attendees
location	VARCHAR(255)	Location of the room
equipment	TEXT[]	Array of equipment available in the room

Bookings Table

Field	Type	Description
booking_id	UUID	Unique identifier for the booking
room_id	UUID	Foreign key referencing the Rooms table
user_id	UUID	Foreign key referencing the Users table
start_time	TIMESTAMP	Start time of the booking
end_time	TIMESTAMP	End time of the booking
meeting_title	VARCHAR	Title of the meeting
description	TEXT	Description of the meeting
recurring	BOOLEAN	Indicates if the booking is recurring
recurrence_rule	TEXT	Rule for recurrence (e.g., RRULE=WEEKLY;BYDAY=MO,TU,WE,TH,FR)

4. Endpoints

Search for available rooms:
- GET /rooms/availability
- Request:

{
  "start_time": "2024-01-22T09:00:00Z",
  "end_time": "2024-01-22T10:00:00Z",
  "attendees": 10
}

*   Response:

[
  {
    "room_id": "...",
    "room_name": "Meeting Room A",
    "capacity": 12
  },
  {
    "room_id": "...",
    "room_name": "Meeting Room B",
    "capacity": 15
  }
]

Book a room:
- POST /bookings
- Request:

{
  "room_id": "...",
  "user_id": "...",
  "start_time": "2024-01-22T09:00:00Z",
  "end_time": "2024-01-22T10:00:00Z",
  "meeting_title": "Daily Stand-up",
  "description": "...",
  "recurring": true,
  "recurrence_rule": "RRULE:FREQ=WEEKLY;BYDAY=MO,TU,WE,TH,FR;COUNT=4"
}

*   Response:

{
  "booking_id": "...",
  "status": "confirmed"
}

Get booking details:
- GET /bookings/{booking_id}
Cancel a booking:
- DELETE /bookings/{booking_id}

5. Tradeoffs

Component	Approach	Pros	Cons	Alternative Approaches	Pros	Cons
Database	Relational (e.g., PostgreSQL)	Strong consistency, ACID properties, well-suited for complex queries and relationships.	Can be more complex to scale horizontally compared to NoSQL databases.	NoSQL (e.g., MongoDB)	Easier horizontal scaling, more flexible schema.	Eventual consistency, less suitable for complex relationships and transactions.
Caching	Redis	Fast in-memory data access, reduces load on the database.	Data invalidation can be challenging.	Memcached	Similar performance characteristics.	Simpler but fewer features than Redis.
Message Queue	Kafka	High throughput, fault-tolerant, suitable for asynchronous tasks like calendar synchronization and reporting.	More complex to set up and manage compared to simpler message queues.	RabbitMQ	Easier to set up and manage.	Lower throughput compared to Kafka.
Calendar Integration	Polling and Webhooks	Supports real-time updates and synchronization.	Complex implementation due to varying calendar API limitations and inconsistencies.	Batch Synchronization	Simpler implementation.	Less real-time synchronization.

6. Other Approaches

NoSQL Database: Using a NoSQL database like MongoDB could offer more flexibility in the data model, especially if the requirements evolve frequently. However, it might require more effort to ensure data consistency and handle complex relationships.
Microservices Architecture: Breaking down the application into smaller, independent microservices (e.g., separate services for room management, user management, and booking management) can improve scalability and maintainability. However, it introduces complexities in inter-service communication and data consistency.
Serverless Architecture: Deploying the services as serverless functions (e.g., AWS Lambda) can reduce operational overhead and improve scalability. However, it can also introduce challenges in managing state and handling long-running tasks.

7. Edge Cases

Double Booking: Implement pessimistic locking or optimistic locking in the database to prevent race conditions and ensure that only one booking is confirmed for a given time slot and room.
Partial Booking Failure: If a recurring booking fails for one or more instances, the system should handle the failure gracefully and notify the user. It should also provide options to retry the failed bookings or cancel the entire series.
Time Zone Handling: Store all times in UTC and convert to the user's time zone for display. Carefully handle daylight saving time transitions.
Room Maintenance: Allow administrators to mark rooms as unavailable for maintenance. The system should prevent bookings during maintenance periods.
External Calendar API Limits: Implement retry mechanisms and caching to handle rate limits imposed by external calendar APIs.

8. Future Considerations

Enhanced Reporting and Analytics: Provide more detailed reports on room utilization, booking patterns, and user behavior. Use these insights to optimize room allocation and resource management.
Integration with Video Conferencing Systems: Automatically provision video conferencing links for meetings and integrate with platforms like Zoom or Microsoft Teams.
Smart Room Features: Integrate with room sensors to automatically adjust lighting, temperature, and other environmental factors based on occupancy.
AI-Powered Booking Assistant: Develop an AI-powered assistant that can help users find the best room based on their needs and preferences.
Support for Different Booking Policies: Implement different booking policies for different types of users or meetings (e.g., priority booking for executives, restrictions on booking duration).

Design a meeting room booking system for a large company.