System requirements

Functional Requirements

1. User Management

• Allow users to register, log in, and manage their profiles.
• Enable users to view their booking history and preferences.
• Support guest checkouts for non-registered users.

2. Hotel Search and Comparison

• Allow users to search hotels based on location, budget, check-in/check-out dates, amenities, and ratings.
• Provide filters for narrowing results (e.g., price range, room type, availability).
• Enable users to compare multiple hotels on parameters like price, amenities, and reviews.

3. Hotel Listings and Management

• Allow hotels to register and manage property details, room availability, and pricing.
• Support adding photos, descriptions, and amenities for each property.
• Provide tools for managing special discounts and promotions.

4. Real-Time Availability Updates

• Display real-time room availability for selected dates.
• Automatically update availability when a booking is made or canceled.

5. Booking Management

• Allow users to book rooms by selecting dates and room types.
• Provide temporary reservation during the checkout process.
• Support cancellation and modification of bookings.

6. Payment Processing

• Support multiple payment methods (credit/debit cards, wallets, UPI, net banking).
• Handle secure payment processing with fraud detection.
• Support partial payments, refundable deposits, and refunds for cancellations.

7. Reviews and Ratings

• Allow users to review and rate hotels after their stay.
• Provide an aggregated rating and review system for each hotel.

8. Notifications and Alerts

• Send booking confirmations and reminders via email, SMS, or in-app notifications.
• Notify users of price drops, promotions, or upcoming trips.

9. Personalized Recommendations

• Provide recommendations based on user preferences, past bookings, and browsing behavior.

10. Admin Dashboard

• Enable administrators to manage hotels, monitor bookings, and handle user support.
• Provide tools for resolving disputes and managing flagged reviews.

Non-Functional Requirements

1. Performance

• Ensure search results are displayed within 1 second.
• Handle real-time availability updates with minimal latency.

2. Scalability

• Support thousands of concurrent users during peak traffic.
• Handle an expanding inventory of hotels and properties.

3. Reliability

• Ensure 99.9% uptime with failover mechanisms and redundancy.
• Implement retry mechanisms for failed payment or booking transactions.

4. Security

• Encrypt sensitive data like user credentials and payment details.
• Comply with PCI-DSS standards for secure payment processing.
• Protect against bots and fraudulent activities with CAPTCHA and activity monitoring.

5. Usability

• Design an intuitive and visually appealing interface for web and mobile platforms.
• Support multi-language and regional customizations.

6. Availability

• Ensure the system is accessible 24/7 with minimal maintenance downtime.
• Use a Content Delivery Network (CDN) for faster content delivery globally.

7. Data Consistency

• Maintain strong consistency for room availability and booking confirmations.
• Allow eventual consistency for less critical data like reviews and recommendations.

8. Maintainability

• Use modular architecture for easier updates and addition of new features.
• Implement logging and monitoring for effective debugging.

9. Privacy

• Adhere to GDPR, CCPA, and other privacy regulations.
• Provide users control over their data, including viewing and deleting stored information.

10. Extensibility

• Allow integration with third-party services (e.g., travel agencies, payment gateways).
• Provide APIs for partners to integrate hotel inventory into their platforms.

Capacity estimation

1. User Base

• Monthly Active Users (MAU): ~10 million users (travelers).
• Daily Active Users (DAU): ~1 million users.
• Concurrent Users: Assume 5% of DAU active simultaneously → ~50,000 concurrent users during peak hours.

2. Hotels and Rooms

• Total Hotels: ~1 million hotels worldwide.
• Rooms Per Hotel: ~50 rooms on average.
• Total Rooms: ~50 million rooms globally.

3. Bookings

• Daily Bookings:
  • Assume 1% of DAU make a booking → ~10,000 bookings/day.
• Peak Booking Requests Per Second:
  • ~20% of daily bookings occur during peak hours → ~2,000 bookings/hour = ~0.56 bookings/second.

4. Searches

• Search Queries Per User:
  • ~5 search queries per user per session.
• Daily Search Queries:
  • ~1 million users * 5 = ~5 million queries/day.
• Peak Search Requests Per Second:
  • ~10% during peak hours → ~500,000 queries/hour = ~140 RPS.

5. Notifications

• Notifications Per Booking:
  • ~3 notifications (booking confirmation, reminder, etc.) per booking.
• Daily Notifications:
  • ~10,000 bookings/day * 3 = ~30,000 notifications/day.
• Peak Notifications Per Second:
  • ~10% during peak hours → ~3,000 notifications/hour = ~0.83 notifications/second.

6. Payment Transactions

• Transactions Per Day:
  • Each booking generates a payment transaction → ~10,000 transactions/day.
• Peak Payment Requests Per Second:
  • ~10% during peak hours → ~1,000 transactions/hour = ~0.28 TPS.

7. Database Size

• Hotel Data:
  • ~1 million hotels * 5 KB/hotel = ~5 GB.
• Room Data:
  • ~50 million rooms * 1 KB/room = ~50 GB.
• Booking Data:
  • ~10,000 bookings/day * 1 KB/booking = ~10 MB/day → ~3.65 GB/year.
• User Data:
  • ~10 million users * 10 KB/user = ~100 GB.
• Review Data:
  • ~100 million reviews (assuming 10 reviews per hotel) * 1 KB/review = ~100 GB.
• Total Yearly Storage: ~250 GB.

8. Bandwidth Requirements

• Search Requests:
  • ~5 million queries/day * 2 KB/request = ~10 GB/day.
• Booking Requests:
  • ~10,000 bookings/day * 5 KB/request = ~50 MB/day.
• Notifications:
  • ~30,000 notifications/day * 1 KB = ~30 MB/day.
• Total Daily Bandwidth: ~10.08 GB/day.

9. Compute Requirements

• API Gateway:
  • Handle ~150 RPS during peak traffic (search, booking, and payment combined).
• Search Service:
  • Serve ~140 RPS during peak traffic for hotel searches.
• Booking Service:
  • Handle ~0.56 RPS for booking confirmations.

API design

1. User Management APIs

1. POST /user/signup
   • Allows users to register by providing name, email, password, and preferences.
2. POST /user/login
   • Authenticates users and returns a session token.
3. GET /user/profile
   • Retrieves user profile details and booking history.
4. PUT /user/profile
   • Updates user information and preferences.
5. DELETE /user/account
   • Deactivates or deletes a user account.

2. Search and Recommendation APIs

1. GET /hotels/search
   • Fetches a list of hotels based on location, dates, and filters (e.g., budget, amenities).
2. GET /hotels/recommendations
   • Provides personalized hotel recommendations based on user preferences and past behavior.
3. GET /hotels/{hotel_id}/details
   • Retrieves detailed information about a specific hotel, including rooms, amenities, and reviews.

3. Booking and Room Management APIs

1. GET /hotels/{hotel_id}/rooms
   • Fetches room availability for a specific hotel and date range.
2. POST /bookings/reserve
   • Temporarily reserves rooms for a user during checkout.
3. POST /bookings/confirm
   • Confirms a booking after successful payment.
4. GET /bookings/{booking_id}
   • Fetches details of a specific booking.
5. POST /bookings/cancel
   • Cancels an existing booking and processes refunds.

4. Payment APIs

1. POST /payments/initialize
   • Initiates a payment transaction for a booking.
2. POST /payments/confirm
   • Confirms payment after successful processing by the payment gateway.
3. GET /payments/{payment_id}/status
   • Checks the status of a payment transaction.
4. POST /payments/refund
   • Initiates a refund for a canceled booking.

5. Reviews and Ratings APIs

1. POST /reviews
   • Allows users to submit reviews and ratings for hotels they’ve stayed in.
2. GET /hotels/{hotel_id}/reviews
   • Retrieves reviews for a specific hotel.
3. POST /reviews/flag
   • Allows users or admins to flag inappropriate reviews.

6. Notifications APIs

1. GET /notifications
   • Retrieves all notifications for a user.
2. POST /notifications/send
   • Sends a notification (e.g., booking confirmation or reminders).
3. POST /notifications/acknowledge
   • Marks a notification as read.

7. Promotions and Offers APIs

1. GET /promotions
   • Fetches all active promotions and discount codes.
2. POST /promotions/apply
   • Validates and applies a discount code to a booking.

8. Admin Management APIs

1. POST /admin/hotel/add
   • Adds a new hotel listing to the system.
2. PUT /admin/hotel/{hotel_id}
   • Updates hotel details, including room availability and pricing.
3. GET /admin/bookings
   • Fetches all bookings for a specific date or hotel.
4. POST /admin/reviews/flagged
   • Handles flagged reviews and takes necessary actions.

9. Analytics APIs

1. GET /analytics/user-activity
   • Fetches user engagement data (e.g., searches, bookings).
2. GET /analytics/hotel-performance
   • Provides insights into hotel occupancy and revenue.
3. GET /analytics/system-usage
   • Monitors system performance and traffic metrics.

10. Hotel Inventory Management APIs (For Hotel Owners)

1. GET /inventory/hotel/{hotel_id}
   • Fetches inventory details for a specific hotel.
2. POST /inventory/room/add
   • Adds new rooms to the inventory.
3. PUT /inventory/room/{room_id}
   • Updates room availability, pricing, or details.

Database design

1. User Database

• Database Schema Details:
  • users table:
    • Attributes: user_id (PK), name, email (unique), password_hash, phone, preferences, created_at, updated_at.
  • user_preferences table:
    • Attributes: user_id (FK), preferred_locations, budget_range, preferred_amenities.
• Purpose:
  • Stores user information, login credentials, and preferences for personalization.
• Tech Used:
  • PostgreSQL
• Trade-Off:
  • Provides strong consistency and supports complex relational queries but requires scaling strategies like read replicas or sharding to handle high traffic.

2. Hotel and Room Database

• Database Schema Details:
  • hotels table:
    • Attributes: hotel_id (PK), name, location, rating, amenities, owner_id (FK), description, created_at.
  • rooms table:
    • Attributes: room_id (PK), hotel_id (FK), room_type, price_per_night, availability_status, capacity.
• Purpose:
  • Stores hotel and room details, including amenities, ratings, and availability.
• Tech Used:
  • MySQL
• Trade-Off:
  • Optimized for structured, relational data but requires indexing and partitioning to handle frequent read/write operations at scale.

3. Booking Database

• Database Schema Details:
  • bookings table:
    • Attributes: booking_id (PK), user_id (FK), hotel_id (FK), room_id (FK), check_in_date, check_out_date, status, total_amount, created_at.
  • booking_status table:
    • Attributes: status_id (PK), status_name (e.g., reserved, confirmed, canceled).
• Purpose:
  • Tracks booking transactions, including room allocations and status updates.
• Tech Used:
  • PostgreSQL
• Trade-Off:
  • Ensures ACID compliance for reliable booking transactions but may experience performance bottlenecks under high concurrency without proper scaling.

4. Payment Database

• Database Schema Details:
  • payments table:
    • Attributes: payment_id (PK), booking_id (FK), user_id (FK), amount, payment_method, status, transaction_time.
  • refunds table:
    • Attributes: refund_id (PK), payment_id (FK), refund_amount, reason, processed_at.
• Purpose:
  • Tracks payment transactions, including successful payments and refunds.
• Tech Used:
  • PostgreSQL
• Trade-Off:
  • Strong consistency ensures reliable financial records but requires advanced indexing and partitioning for high-frequency transactions.

5. Reviews and Ratings Database

• Database Schema Details:
  • reviews table:
    • Attributes: review_id (PK), hotel_id (FK), user_id (FK), rating, comment, created_at.
  • flags table:
    • Attributes: flag_id (PK), review_id (FK), flag_reason, reviewed_by, action_taken.
• Purpose:
  • Stores user-generated reviews and tracks flagged reviews for moderation.
• Tech Used:
  • MongoDB
• Trade-Off:
  • Flexible schema supports dynamic data but lacks strong consistency, which can be an issue for analytics requiring accurate aggregations.

6. Notification Database

• Database Schema Details:
  • notifications table:
    • Attributes: notification_id (PK), user_id (FK), message, type, status, created_at.
• Purpose:
  • Manages user-specific notifications and delivery statuses.
• Tech Used:
  • Redis for real-time delivery and PostgreSQL for persistent storage.
• Trade-Off:
  • Redis ensures low-latency delivery but sacrifices durability, requiring periodic synchronization with PostgreSQL for data recovery.

7. Search Index Database

• Database Schema Details:
  • search_index:
    • Attributes: hotel_id, name, location, rating, price_range, amenities.
• Purpose:
  • Facilitates fast and efficient hotel searches based on user queries.
• Tech Used:
  • Elasticsearch
• Trade-Off:
  • Provides exceptional performance for full-text and geospatial queries but requires significant computational resources and can be complex to scale.

8. Analytics Database

• Database Schema Details:
  • booking_metrics table:
    • Attributes: metric_id (PK), hotel_id, total_bookings, revenue, date.
  • user_engagement table:
    • Attributes: engagement_id (PK), user_id, search_queries, bookings_made, last_active.
• Purpose:
  • Aggregates and analyzes data for insights into user behavior and hotel performance.
• Tech Used:
  • Google BigQuery or Amazon Redshift
• Trade-Off:
  • Handles large-scale analytical queries efficiently but introduces higher latency for real-time queries.

High-level design

1. User Interface (UI)

• Overview:
  • Provides web and mobile applications for users to interact with the platform.
• Features:
  • Allows users to search for hotels, view details, compare options, and complete bookings.
  • Enables hotel owners to manage properties and bookings via an admin interface.

2. API Gateway

• Overview:
  • Acts as a single entry point for all client requests.
• Features:
  • Routes requests to the appropriate backend services.
  • Handles authentication, rate limiting, and logging.

3. User Management Service

• Overview:
  • Manages user registration, login, profile updates, and preferences.
• Features:
  • Stores and retrieves user data securely.
  • Supports personalization through preferences and past interactions.

4. Hotel and Room Management Service

• Overview:
  • Handles hotel listings, room details, and availability.
• Features:
  • Allows hotel owners to add and manage properties.
  • Updates real-time room availability for users.

5. Search and Recommendation Service

• Overview:
  • Provides search functionality for hotels and personalized recommendations.
• Features:
  • Supports filters (e.g., location, price range, ratings).
  • Leverages user behavior to suggest relevant hotels.

6. Booking Service

• Overview:
  • Manages the end-to-end booking process, including seat reservations.
• Features:
  • Ensures real-time room availability updates.
  • Handles booking status transitions (e.g., reserved, confirmed, canceled).

7. Payment Service

• Overview:
  • Handles payment processing and refund management.
• Features:
  • Integrates with multiple payment gateways.
  • Ensures secure transactions and provides payment status tracking.

8. Notification Service

• Overview:
  • Sends real-time notifications to users and hotel owners.
• Features:
  • Delivers booking confirmations, reminders, and promotional offers.
  • Supports SMS, email, and in-app notifications.

9. Review and Rating Service

• Overview:
  • Manages user-generated reviews and ratings for hotels.
• Features:
  • Allows users to leave reviews and ratings post-stay.
  • Tracks flagged reviews for moderation.

10. Admin Dashboard

• Overview:
  • Provides tools for administrators to monitor and manage the platform.
• Features:
  • Enables handling of user disputes, flagged reviews, and system-wide analytics.

11. Analytics and Reporting Service

• Overview:
  • Aggregates and analyzes data for insights into system performance and user behavior.
• Features:
  • Provides dashboards for bookings, revenue, and user engagement metrics.

12. Real-Time Availability Service

• Overview:
  • Tracks and updates room availability across the platform.
• Features:
  • Ensures consistency for room status during high traffic.
  • Prevents overbooking with real-time synchronization.

13. Load Balancer

• Overview:
  • Distributes incoming traffic across backend services to prevent overload.
• Features:
  • Ensures high availability and fault tolerance for the system.

14. Search Index

• Overview:
  • Optimized for fast hotel searches and filters.
• Features:
  • Uses Elasticsearch for full-text search and geospatial queries.

15. Content Delivery Network (CDN)

• Overview:
  • Optimizes delivery of static assets like hotel images and descriptions.
• Features:
  • Reduces latency for globally distributed users.

16. Data Pipeline

• Overview:
  • Processes real-time and batch data for analytics and reporting.
• Features:
  • Streams booking, payment, and user engagement data to the analytics service.

17. Machine Learning Engine

• Overview:
  • Powers personalization and fraud detection features.
• Features:
  • Provides recommendations based on user behavior.
  • Flags suspicious activities in payments or bookings.

Request flows

1. User Registration

1. User Interaction:
   • User provides personal details (name, email, password).
2. API Gateway:
   • Routes the request to the User Management Service.
3. User Management Service:
   • Validates input data and hashes the password.
   • Stores user details in the User Database.
4. Database Interaction:
   • Inserts new user data into the users table.
5. Response:
   • Returns a success message with a user ID.

2. Hotel Search

1. User Interaction:
   • User searches for hotels by location, dates, and filters.
2. API Gateway:
   • Routes the request to the Search Service.
3. Search Service:
   • Queries the Search Index for matching hotels based on the filters.
   • Retrieves hotel details from the Hotel and Room Management Service.
4. Database Interaction:
   • Fetches hotel metadata from the hotels table and available rooms from the rooms table.
5. Response:
   • Returns a list of matching hotels with room availability and pricing.

3. Hotel Details Request

1. User Interaction:
   • User selects a hotel to view detailed information.
2. API Gateway:
   • Routes the request to the Hotel and Room Management Service.
3. Hotel and Room Management Service:
   • Fetches detailed hotel data, including amenities, reviews, and images.
4. Database Interaction:
   • Queries the hotels, rooms, and reviews tables.
5. Response:
   • Returns detailed hotel information.

4. Booking Request

1. User Interaction:
   • User selects room(s), check-in/check-out dates, and proceeds to booking.
2. API Gateway:
   • Routes the request to the Booking Service.
3. Booking Service:
   • Validates room availability and temporarily reserves the selected rooms.
4. Database Interaction:
   • Updates the rooms table to mark the rooms as "reserved".
5. Response:
   • Confirms temporary reservation and proceeds to payment.

5. Payment Processing

1. User Interaction:
   • User initiates payment using a selected payment method.
2. API Gateway:
   • Routes the request to the Payment Service.
3. Payment Service:
   • Validates payment details and sends the transaction to the Payment Gateway.
4. Payment Gateway Interaction:
   • Processes the payment and returns the transaction status.
5. Database Interaction:
   • Records payment details in the payments table.
6. Response:
   • Confirms payment success and updates booking status to "confirmed".

6. Booking Confirmation

1. Booking Service:
   • Marks the reserved rooms as "booked" in the rooms table.
2. Notification Service:
   • Sends booking confirmation via email, SMS, or push notification.
3. Database Interaction:
   • Updates the bookings table with the booking status and details.
4. Response:
   • Displays booking confirmation with ticket or receipt details.

7. Cancellation Request

1. User Interaction:
   • User requests to cancel a booking.
2. API Gateway:
   • Routes the request to the Booking Service.
3. Booking Service:
   • Validates cancellation policies and updates booking status to "canceled".
4. Payment Service:
   • Initiates a refund process if applicable.
5. Database Interaction:
   • Updates the bookings table and refunds details in the payments table.
6. Response:
   • Confirms cancellation and refund status.

8. Reviews and Ratings

1. User Interaction:
   • User submits a review and rating for a hotel post-stay.
2. API Gateway:
   • Routes the request to the Review and Rating Service.
3. Review and Rating Service:
   • Validates input and stores the review.
4. Database Interaction:
   • Inserts data into the reviews table.
5. Response:
   • Confirms successful submission of the review.

9. Notifications

1. Trigger Event:
   • A booking, payment, or promotional event occurs.
2. Notification Service:
   • Creates a notification event and queues it for delivery.
3. Database Interaction:
   • Logs the notification in the notifications table.
4. Delivery:
   • Sends the notification via the user’s preferred channel.
5. Response:
   • Confirms notification delivery status.

10. Admin Requests

1. Admin Interaction:
   • Admin adds or updates hotel listings or monitors flagged reviews.
2. API Gateway:
   • Routes the request to the Admin Dashboard Service.
3. Admin Service:
   • Updates hotel data or processes flagged reviews.
4. Database Interaction:
   • Modifies entries in the hotels or reviews tables.
5. Response:
   • Confirms successful update or action.

Detailed component design

1. User Management Service

End-to-End Working

The User Management Service handles all user-related activities, including registration, login, profile updates, and retrieving preferences. During registration, user-provided data is validated, and passwords are hashed using a secure algorithm (e.g., bcrypt) before being stored in the database. Login requests validate user credentials against stored records and issue a session token (e.g., JWT) for subsequent interactions. When users request profile updates or retrieve preferences, the service queries the database and ensures efficient caching for frequently accessed data.

Data Structures and Algorithms Used

The service employs a relational schema:

• users table: Stores user details (user_id, email, password_hash, preferences).
• user_preferences table: Stores preferences like location, budget range, and preferred amenities. For authentication, JWT tokens are used for stateless, secure session management. Redis caches frequently accessed user sessions and preferences, reducing database reads.

How Peak Traffic is Handled

To handle high traffic:

1. Horizontal Scaling: Adds multiple instances of the service behind a load balancer.
2. Caching: Uses Redis to store frequently accessed user data (e.g., sessions, preferences) to reduce load on the database.
3. Read-Replicas: Database replicas handle read-heavy operations like retrieving user profiles.

Edge Cases and Handling

1. Duplicate Registrations:
   • Enforced by unique constraints on email and phone fields in the database.
2. Forgotten Passwords:
   • Securely handled with token-based password reset workflows using email or SMS.
3. Session Hijacking:
   • Mitigated by token expiration and monitoring for unusual login locations or devices.

2. Hotel and Room Management Service

End-to-End Working

The Hotel and Room Management Service is responsible for storing and updating hotel listings, room details, and availability. Hotel owners use this service to add or modify property information, while users retrieve details like amenities, pricing, and reviews. Real-time availability updates are synchronized with the Booking Service whenever a booking or cancellation occurs.

Data Structures and Algorithms Used

• Relational Schema:
  • hotels table for storing metadata (hotel_id, name, location, rating).
  • rooms table for room-level details (room_id, price, availability_status).
• Indexing:
  • Indexed fields (e.g., location, rating) optimize queries for large datasets.
• Geohashing:
  • Encodes latitude and longitude for efficient spatial searches.

How Peak Traffic is Handled

1. CDN Integration: Hotel images and static content are served through CDNs to reduce backend load.
2. Sharding: Database tables are partitioned by region to distribute query load geographically.
3. Caching: Frequently searched hotel data is cached in Redis or Elasticsearch for faster retrieval.

Edge Cases and Handling

1. Overlapping Room Availability Updates:
   • Resolved using transaction locks to ensure consistency during concurrent updates.
2. Data Sync Failures:
   • Regularly scheduled jobs ensure synchronization between hotel and booking data.
3. Invalid Property Details:
   • Validated on the admin dashboard before changes are committed.

3. Booking Service

End-to-End Working

The Booking Service manages the entire booking lifecycle, from room selection to confirmation. When a user selects a room, the service validates availability and temporarily reserves the room during checkout. After payment confirmation, it marks the room as "booked". If payment fails or the session expires, the reserved status is released, making the room available for others.

Data Structures and Algorithms Used

• Relational Schema:
  • bookings table tracks transactions (booking_id, user_id, status).
  • rooms table updates availability_status to "reserved" or "booked".
• Row-Level Locking:
  • Prevents double booking by locking rows during availability checks.
• ACID Transactions:
  • Ensures atomicity when updating room availability and booking status.

How Peak Traffic is Handled

1. Partitioning: Room data is partitioned by hotel_id and date to reduce contention.
2. Caching: Room availability is cached for high-demand properties to reduce database queries.
3. Queueing: Asynchronous processing of non-critical updates (e.g., booking confirmations) with message queues (e.g., Kafka).

Edge Cases and Handling

1. Double Booking:
   • Prevented with row-level locks and transaction isolation during concurrent updates.
2. Payment Timeout:
   • Automatically releases reserved rooms if payment is not completed within a time limit.
3. Cancelled Bookings:
   • Updates room status immediately and issues refunds via the Payment Service.

4. Payment Service

End-to-End Working

The Payment Service processes user transactions securely. Upon receiving a payment request, it validates the payment details and forwards them to a third-party payment gateway. After the gateway confirms the transaction, the service updates the booking status. In case of cancellations, refunds are initiated automatically.

Data Structures and Algorithms Used

• Relational Schema:
  • payments table stores transaction details (payment_id, booking_id, amount).
  • refunds table tracks refund transactions (refund_id, payment_id, status).
• Encryption:
  • Ensures secure storage and transmission of sensitive data (e.g., card details).

How Peak Traffic is Handled

1. Multiple Gateways: Traffic is distributed across multiple payment gateways to avoid bottlenecks.
2. Batch Processing: Groups smaller transactions into batches during peak periods.
3. Retry Mechanisms: Failed transactions are retried automatically with exponential backoff.

Edge Cases and Handling

1. Gateway Downtime:
   • Automatically switches to alternate gateways or queues the transaction for retry.
2. Partial Payments:
   • Marks the booking as pending and notifies the user to complete the payment.
3. Fraudulent Transactions:
   • Flags suspicious activities using fraud detection algorithms.

5. Search Service

End-to-End Working

The Search Service handles hotel searches based on user queries, applying filters like location, price range, and ratings. Results are ranked for relevance and fetched from the Search Index. This service integrates with the Hotel and Room Management Service for real-time updates.

Data Structures and Algorithms Used

• Elasticsearch:
  • Builds an inverted index for fast full-text searches and geospatial queries.
• Geospatial Queries:
  • Uses Haversine Formula to calculate distances for proximity-based searches.
• Ranking Algorithms:
  • Implements relevance scoring (e.g., BM25) to rank search results.

How Peak Traffic is Handled

1. Sharded Index: Divides the search index by region to distribute query load.
2. Result Caching: Caches frequent queries and their results in memory.
3. Horizontal Scaling: Adds Elasticsearch nodes during high demand.

Edge Cases and Handling

1. No Results Found:
   • Suggests alternative hotels based on nearby locations or similar preferences.
2. Search Query Errors:
   • Implements fuzzy matching to handle typos in user queries.
3. Stale Index Data:
   • Periodic synchronization ensures the search index remains up-to-date.

Trade offs/Tech choices

Relational vs NoSQL Databases:

• Choice: Relational databases (PostgreSQL, MySQL) for user, booking, and payment data due to strong consistency and ACID compliance.
• Trade-Off: Increased complexity in scaling compared to NoSQL databases.

Elasticsearch for Search:

• Choice: Elasticsearch for fast, full-text, and geospatial queries.
• Trade-Off: High resource consumption but necessary for low-latency search performance.

Redis for Real-Time Data:

• Choice: Redis for caching availability and user session data.
• Trade-Off: Limited persistence requires periodic synchronization with the main database.

Multiple Payment Gateways:

• Choice: Integrated multiple gateways for high availability.
• Trade-Off: Increased operational complexity for gateway selection and fallback handling.

Microservices Architecture:

• Choice: Microservices for modularity and scalability.
• Trade-Off: Added overhead in managing service communication and debugging.

Failure scenarios/bottlenecks

Database Overload:

• Issue: High read/write traffic during peak times.
• Mitigation: Use caching, sharding, and read replicas.

Payment Gateway Downtime:

• Issue: Failed transactions due to gateway unavailability.
• Mitigation: Integrate multiple gateways and implement retry mechanisms.

Double Booking:

• Issue: Concurrent users reserving the same room.
• Mitigation: Use row-level locking and transaction isolation.

Search Index Overload:

• Issue: High volume of search queries affecting performance.
• Mitigation: Implement sharding, horizontal scaling, and result caching.

Notification Delays:

• Issue: Large volume of notifications during peak hours.
• Mitigation: Scale worker pools and prioritize time-sensitive notifications.

Data Sync Failures:

• Issue: Inconsistent room availability between booking and room services.
• Mitigation: Periodic sync jobs and real-time updates via message queues.

Fraudulent Activities:

• Issue: Fake bookings or payment fraud.
• Mitigation: Use ML-based fraud detection and monitoring.

Future improvements

Dynamic Scaling:

• Improvement: Implement auto-scaling for microservices and databases.
• Mitigation: Handles database overload and peak traffic efficiently.

Enhanced Caching:

• Improvement: Cache search results and frequently accessed data more effectively.
• Mitigation: Reduces load on databases and search index during spikes.

Optimized Payment Handling:

• Improvement: Add more payment gateways and optimize retries.
• Mitigation: Addresses gateway downtimes and failed transactions.

Real-Time Data Synchronization:

• Improvement: Use event-driven architecture for instant updates.
• Mitigation: Ensures consistency in room availability and booking data.

Fraud Detection Models:

• Improvement: Deploy advanced machine learning models for anomaly detection.
• Mitigation: Reduces the risk of fraudulent bookings or payments.

Search Service Scaling:

• Improvement: Dynamically shard the search index based on traffic patterns.
• Mitigation: Prevents bottlenecks during high search query volumes.

Streamlined Notification System:

• Improvement: Introduce batch processing for non-critical notifications.
• Mitigation: Reduces delays in notification delivery during peak demand.