Let's design a room reservation system. Consider the following requirements:

1. Users: The system should allow users to search for available rooms and make reservations.
2. Rooms: Each room has a capacity, a list of available equipment (e.g., projector, whiteboard), and a location.
3. Reservations: Reservations have a start time, an end time, a room, and a user.
4. Conflicts: The system must prevent double-booking of rooms. If someone tries to book a room that is already booked during that timeframe, they should receive an error message.
5. Searching: Users should be able to search for rooms based on criteria such as capacity, available equipment, location, and time slot.
6. Admin: Admins should be able to add new rooms, modify room details, and view all reservations.

Consider the data models, APIs, and system architecture. Provide a high-level overview of your design, including the key components and their interactions. What data structures would you use to efficiently store and retrieve room and reservation information? How would you handle concurrency and prevent race conditions when multiple users try to book the same room simultaneously? What are the trade-offs between different architectural choices (e.g., monolithic vs. microservices)? What API endpoints would you expose for common operations like searching for rooms, creating reservations, and canceling reservations? How would you handle edge cases such as overlapping reservations or invalid user input? What database technology would you use and why?

Room Reservation System Design

Let's design a room reservation system, considering the specified requirements and covering data models, APIs, architecture, and potential challenges.

1. Requirements

• Users: Authenticated users can search for available rooms and make/cancel reservations.
• Rooms: Rooms have attributes like capacity, available equipment, location, and unique identifier.
• Reservations: Reservations include a start time, end time, associated room, and user making the reservation.
• Conflicts: The system prevents double-booking of rooms during overlapping time slots.
• Searching: Users can search rooms based on capacity, equipment, location, and time slot availability.
• Admin: Administrators can add/modify room details, and view/manage all reservations.

2. High-Level Design

The system architecture will comprise the following components:

• User Interface (UI): Web or mobile application for users and admins to interact with the system.
• API Gateway: Entry point for all requests, handling authentication, routing, and rate limiting.
• Authentication Service: Manages user accounts, authentication, and authorization.
• Room Service: Manages room information (add, update, retrieve).
• Reservation Service: Handles reservation creation, cancellation, conflict detection, and retrieval.
• Search Service: Provides room search functionality based on specified criteria.
• Database: Persistent storage for rooms, users, and reservation data.

Component Interaction:

1. User interacts with the UI to search for rooms or create reservations.
2. UI sends requests to the API Gateway.
3. API Gateway authenticates the user via the Authentication Service.
4. API Gateway routes the request to the appropriate service (Room Service, Reservation Service, Search Service).
5. Services interact with the database to retrieve or update data.
6. Services return the results to the API Gateway.
7. API Gateway returns the results to the UI.

3. Data Model

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

Tables:

• Users

  Field	Type	Description
  user_id	UUID	Primary key, unique user identifier
  username	VARCHAR(255)	User's login name
  password_hash	VARCHAR(255)	Hashed password
  email	VARCHAR(255)	User's email address
  role	VARCHAR(50)	User's role (e.g., user, admin)

• Rooms

  Field	Type	Description
  room_id	UUID	Primary key, unique room identifier
  name	VARCHAR(255)	Room name
  capacity	INTEGER	Maximum capacity of the room
  location	VARCHAR(255)	Room location
  equipment	TEXT[]	Array of available equipment (e.g., projector, whiteboard)

• Reservations

  Field	Type	Description
  reservation_id	UUID	Primary key, unique reservation identifier
  room_id	UUID	Foreign key referencing Rooms(room_id)
  user_id	UUID	Foreign key referencing Users(user_id)
  start_time	TIMESTAMP	Reservation start time
  end_time	TIMESTAMP	Reservation end time

4. Endpoints

Here are some key API endpoints:

• Search Rooms:

  • GET /rooms?capacity={capacity}&equipment={equipment}&location={location}&start_time={start_time}&end_time={end_time}
  • Request Parameters: Capacity (optional), Equipment (optional), Location (optional), Start Time (optional), End Time (optional)
  • Response: JSON array of available rooms matching the criteria.

• Create Reservation:

  • POST /reservations
  • Request Body: { room_id, user_id, start_time, end_time }
  • Response: Reservation ID or error message if conflict exists.

• Cancel Reservation:

  • DELETE /reservations/{reservation_id}
  • Response: Success/failure message.

• Get Room Details:

  • GET /rooms/{room_id}
  • Response: Room details (JSON).

• Add Room (Admin):

  • POST /rooms
  • Request Body: Room details (name, capacity, location, equipment).
  • Response: Room ID of the newly created room.

• Update Room (Admin):

  • PUT /rooms/{room_id}
  • Request Body: Updated room details.
  • Response: Success/failure message.

5. Tradeoffs

Component	Approach	Pros	Cons
Architecture	Microservices	Scalability, independent deployments, technology diversity	Increased complexity, inter-service communication overhead, distributed tracing
Architecture	Monolithic	Simpler development, easier deployment, lower operational overhead	Scalability limitations, single point of failure, tight coupling
Database	Relational (SQL)	ACID properties, strong consistency, mature technology, well-defined schema	Scaling can be complex, may not be optimal for unstructured data
Database	NoSQL (e.g., MongoDB)	Flexible schema, horizontal scalability, better performance for specific workloads	Eventual consistency, less mature, complex transactions
Conflict Detection	Optimistic Locking	Simpler to implement	Higher chance of conflicts, requires retries
Conflict Detection	Pessimistic Locking	Lower chance of conflicts	Reduced concurrency, potential for deadlocks

For this specific system, a microservices architecture offers better scalability and independent deployments, especially if future enhancements are planned. PostgreSQL offers ACID properties for financial transactions. The choice between optimistic and pessimistic locking depends on the expected concurrency level; optimistic locking is suitable if conflicts are rare.

6. Other Approaches

• Monolithic Architecture: A single application encompassing all services. Easier to develop and deploy initially, but difficult to scale and maintain as the system grows.
• NoSQL Database (e.g., MongoDB): Can be used for more flexible data storage, but requires careful consideration of consistency and transaction management.

7. Edge Cases

• Overlapping Reservations: Prevent users from creating reservations that overlap with existing ones. Implement conflict detection logic in the Reservation Service.
• Invalid User Input: Validate all user input (e.g., date formats, capacity limits) to prevent errors and security vulnerabilities.
• Concurrent Reservations: Handle concurrent requests for the same room using locking mechanisms (optimistic or pessimistic) in the database.
• Room Deletion with Active Reservations: Prevent admins from deleting rooms that have active reservations or implement a cascading deletion mechanism (with appropriate warnings).
• Time Zone Handling: Ensure consistent time zone handling across the system to avoid scheduling conflicts. Store all times in UTC.
• Network Issues: Implement retry mechanisms and circuit breakers to handle temporary network outages during inter-service communication.

8. Future Considerations

• Real-time Availability Updates: Implement real-time availability updates using WebSockets or Server-Sent Events (SSE) to provide a more responsive user experience.
• Integration with Calendar Systems: Integrate with external calendar systems (e.g., Google Calendar, Outlook) to allow users to manage their reservations more easily.
• Reporting and Analytics: Add reporting and analytics features to track room utilization, popular time slots, and other relevant metrics.
• Automated Room Release: Automatically release rooms if users don't check-in within a certain timeframe.
• Scalability Enhancements: Implement caching, load balancing, and database sharding to handle increasing traffic and data volume.
• Mobile App: Develop native mobile apps for iOS and Android to provide a better user experience on mobile devices.

9. Database Technology Choice

PostgreSQL is a suitable choice for the database due to its strong ACID properties, support for complex queries, and scalability. It also has excellent support for concurrency and transactions, which is important for preventing double-booking.