System requirements

Functional Requirements

User Management
- Allow users to sign up, log in, and manage profiles.
- Enable users to save favorite locations and preferences.
Business Listings
- Display information for local establishments (e.g., name, category, address, contact, opening hours).
- Allow users to search, filter, and sort businesses by location, category, and rating.
- Support business owners to claim and update their listings.
Review System
- Enable users to write, edit, and delete reviews for businesses.
- Allow users to rate businesses using a standardized system (e.g., stars).
- Display aggregated ratings and reviews for each business.
Search and Recommendation
- Provide search functionality with filters (e.g., price range, proximity, popularity).
- Offer personalized recommendations based on user history and preferences.
Photo Upload
- Allow users to upload photos for businesses as part of their reviews.
- Display user-uploaded photos on business profiles.
Location-Based Services
- Enable users to search for nearby businesses using geolocation.
- Show businesses on an interactive map.
Analytics and Insights
- Display analytics to business owners (e.g., views, clicks, and reviews).
- Provide administrators with system-wide statistics.
Notifications
- Notify users of responses to their reviews or updates on businesses they follow.
- Inform business owners of new reviews or changes in their listing.
Moderation
- Implement mechanisms for flagging inappropriate reviews or photos.
- Provide admins tools to review and act on reported content.
Offline Access
- Allow users to save businesses or reviews for offline access.

Non-Functional Requirements

Performance
- Support low-latency responses for search and listing queries (<200ms).
- Handle thousands of concurrent users during peak traffic.
Scalability
- Ensure horizontal scalability to handle increasing users and reviews.
- Use sharded databases and distributed search engines.
Availability
- Provide 99.9% uptime with failover and redundancy mechanisms.
Security
- Protect user data with encryption (at rest and in transit).
- Prevent spam and fraud with rate limiting and CAPTCHA.
Usability
- Offer an intuitive user interface across web and mobile platforms.
- Support multiple languages and regional preferences.
Data Consistency
- Ensure strong consistency for user-submitted reviews and ratings.
- Support eventual consistency for search indices and recommendations.
Maintainability
- Use modular architecture for easier updates and feature additions.
- Provide detailed logging and monitoring for debugging.
Privacy
- Comply with privacy regulations like GDPR.
- Allow users to manage and delete their reviews or personal data.
Extensibility
- Enable integration with third-party APIs for reservations or promotions.
- Support APIs for developers to build extensions or analytics.
Search Optimization
- Use a search engine (e.g., Elasticsearch) to handle text and geospatial queries.
- Provide fast autocomplete and relevance-based ranking.

Capacity estimation

1. User Base

Monthly Active Users (MAU): ~10 million.
Daily Active Users (DAU): ~1 million.
Concurrent Users: Assume 1% of DAU active at the same time → ~10,000 concurrent users.

2. Business Listings

Total Listings: ~1 million businesses.
Average Reviews/Business: 100 reviews/business.
Photos/Business: 50 photos/business.
Total Data Size:
- Reviews: 1 million * 100 reviews * 1 KB/review ≈ 100 GB.
- Photos: 1 million * 50 photos * 500 KB/photo ≈ 25 TB.

3. Reviews

Daily Reviews: ~1 million users, 5 reviews/day → ~5 million reviews/day.
Storage Requirements:
- 5 million reviews/day * 1 KB/review = ~5 GB/day → ~1.8 TB/year.

4. Photos

Daily Photo Uploads: ~2 million photos/day.
Storage Requirements:
- 2 million photos/day * 500 KB/photo = ~1 TB/day → ~365 TB/year.

5. Search Queries

Search Volume: ~10 searches/user/day.
Total Queries/Day: 1 million users * 10 searches = 10 million queries/day.
Peak Queries/Second: ~10,000 QPS during peak hours.

6. Notifications

Notifications:
- ~5 million daily reviews generate ~5 million notifications.
- Assume 10% users enable push notifications = ~500,000 notifications/day.

7. Database Size

User Data:
- 10 million users * 10 KB/user = 100 GB.
Business Data:
- 1 million businesses * 50 KB/business = 50 GB.
Search Index:
- 1 million businesses + 100 million reviews ≈ ~10 GB.

8. Bandwidth

Review and Photo Uploads:
- ~2 TB/day for photos + ~5 GB/day for reviews → ~2.005 TB/day.
Search Requests:
- 10 million queries/day * ~5 KB/query = ~50 GB/day.
Notifications:
- 500,000 notifications * 1 KB = ~500 MB/day.

9. Compute Requirements

API Gateway:
- Handle ~10,000 concurrent requests.
Search Service:
- Serve ~10,000 QPS with low latency (<200 ms).
Photo Service:
- Upload/download ~2 TB/day.

Summary

Storage:
- Total: ~500 TB/year (including photos, reviews, and metadata).
Traffic:
- ~2 TB/day for photos + 100 GB/day for other activities.
Compute:
- ~10,000 concurrent users, 10,000 QPS for search, scalable to higher peaks.

API design

1. User Management APIs

POST /user/signup
- Registers a new user with email, password, and optional profile details.
POST /user/login
- Authenticates a user and returns an access token.
GET /user/profile
- Fetches the user’s profile details.
PUT /user/profile
- Updates the user’s profile information.
DELETE /user/account
- Deletes the user’s account.

2. Business Listing APIs

GET /business/search
- Search businesses with filters (e.g., location, category, rating).
GET /business/{id}
- Fetch details for a specific business.
POST /business/claim
- Allows business owners to claim their business listing.
POST /business/create
- Adds a new business listing (admin or verified owner only).
PUT /business/{id}
- Updates business details (admin or verified owner only).

3. Review APIs

POST /review
- Submit a new review for a business.
GET /business/{id}/reviews
- Fetch reviews for a specific business.
PUT /review/{id}
- Edit an existing review.
DELETE /review/{id}
- Remove a review.

4. Photo APIs

POST /photo
- Upload a photo for a specific business.
GET /business/{id}/photos
- Retrieve all photos for a business.
DELETE /photo/{id}
- Remove a photo (admin or uploader only).

5. Search and Recommendation APIs

GET /search/autocomplete
- Fetch autocomplete suggestions for search queries.
GET /search/popular
- Fetch popular searches or trending locations.
GET /recommendations
- Fetch personalized recommendations for the user.

6. Notification APIs

GET /notifications
- Retrieve user notifications (e.g., new reviews, responses).
POST /notifications/mark-read
- Mark a notification as read.
POST /notifications/flag
- Report inappropriate notifications or responses.

7. Moderation APIs

POST /moderation/flag
- Flag inappropriate reviews or photos.
GET /moderation/queue
- Fetch flagged content for admin review.
PUT /moderation/{id}
- Approve or reject flagged content.

8. Analytics APIs

GET /business/{id}/analytics
- Provide analytics for a specific business (views, clicks, reviews).
GET /admin/analytics
- Platform-wide statistics for administrators.

9. Miscellaneous APIs

GET /location/nearby
- Fetch nearby businesses using geolocation.
GET /categories
- Retrieve a list of supported business categories.
GET /offline/download
- Download offline data for a region.

Database design

1. User Database

Attributes Stored and Keys:
- users table:
  - Attributes: user_id (PK), name, email (unique), password_hash, preferences, created_at.
  - Primary Key (PK): user_id.
  - No Foreign Keys (FK).
Purpose:
- Manage user profiles, authentication details, and preferences.
Tech Used:
- PostgreSQL
Reason:
- Relational model ensures strong consistency and supports complex queries for user data.

2. Business Database

Attributes Stored and Keys:
- businesses table:
  - Attributes: business_id (PK), name, category, location, contact_info, claimed_by (FK).
  - Primary Key (PK): business_id.
  - Foreign Key (FK): claimed_by references users.user_id.
Purpose:
- Store business listings and metadata for search and filtering.
Tech Used:
- MySQL
Reason:
- Optimized for structured data with frequent queries, sorting, and filtering.

3. Review and Rating Database

Attributes Stored and Keys:
- reviews table:
  - Attributes: review_id (PK), business_id (FK), user_id (FK), rating, review_text, created_at, updated_at.
  - Primary Key (PK): review_id.
  - Foreign Keys (FK):
    - business_id references businesses.business_id.
    - user_id references users.user_id.
Purpose:
- Manage user-submitted reviews, ratings, and associated metadata.
Tech Used:
- MongoDB
Reason:
- Flexible schema for dynamic and diverse review content.

4. Photo Storage

Attributes Stored and Keys:
- photos table:
  - Attributes: photo_id (PK), business_id (FK), uploader_id (FK), photo_url, created_at.
  - Primary Key (PK): photo_id.
  - Foreign Keys (FK):
    - business_id references businesses.business_id.
    - uploader_id references users.user_id.
Purpose:
- Store metadata of user-uploaded photos for businesses.
Tech Used:
- AWS S3 (photo storage) and PostgreSQL (metadata).
Reason:
- Object storage for scalable photo handling, relational DB for efficient metadata queries.

5. Search Index Database

Attributes Stored and Keys:
- search_index:
  - Attributes: business_id, name, category, location, keywords.
  - No Primary or Foreign Keys as it is an index.
Purpose:
- Support full-text and geospatial search for businesses and reviews.
Tech Used:
- Elasticsearch
Reason:
- Optimized for fast, relevance-based search and proximity queries.

6. Analytics Database

Attributes Stored and Keys:
- business_analytics table:
  - Attributes: business_id (PK), views, clicks, reviews_count, timestamp.
  - Primary Key (PK): business_id.
- platform_analytics table:
  - Attributes: metric_id (PK), active_users, reviews_posted, photos_uploaded, timestamp.
  - Primary Key (PK): metric_id.
Purpose:
- Track business performance and system-wide metrics for analysis.
Tech Used:
- Amazon Redshift or Google BigQuery
Reason:
- Optimized for OLAP queries and large-scale analytics.

erDiagram
    USER ||--o{ REVIEW : "writes"
    USER ||--o{ PHOTO : "uploads"
    USER ||--o{ NOTIFICATION : "receives"
    USER }|..|{ BUSINESS-CLAIM : "owns"

    BUSINESS ||--o{ REVIEW : "receives"
    BUSINESS ||--o{ PHOTO : "contains"
    BUSINESS ||--|{ CATEGORY : "belongs to"
    BUSINESS ||--o{ NOTIFICATION : "triggers"

    REVIEW ||--|{ FLAG : "is flagged by"
    REVIEW ||--|{ RATING : "has a"

    PHOTO ||--|{ FLAG : "is flagged by"

    CATEGORY ||--|{ BUSINESS : "categorizes"
    BUSINESS-CLAIM ||--|{ BUSINESS : "for"

High-level design

1. User Interface (UI)

Overview:
- Web and mobile applications that users interact with to explore businesses, write reviews, and view recommendations.
Features:
- User-friendly search, filters, and business browsing.
- Features for adding reviews, uploading photos, and viewing analytics (for business owners).

2. API Gateway

Overview:
- Acts as a single entry point for all client requests, routing them to the appropriate services.
Features:
- Authentication, rate limiting, request validation, and routing.
- Centralized monitoring and logging for all requests.

3. User Management Service

Overview:
- Handles user registration, login, profile management, and authentication.
Features:
- Password hashing, token management, and session handling.

4. Business Management Service

Overview:
- Manages business listings, categories, and ownership claims.
Features:
- CRUD operations for businesses, owner verification, and updates.

5. Review Management Service

Overview:
- Handles user reviews and ratings for businesses.
Features:
- CRUD operations for reviews, flagging inappropriate content, and aggregating ratings.

6. Photo Management Service

Overview:
- Manages uploading, storing, and retrieving photos associated with businesses.
Features:
- Processes metadata and integrates with a scalable storage service (e.g., AWS S3).

7. Search Service

Overview:
- Enables users to search for businesses, reviews, and categories.
Features:
- Full-text search, geospatial queries, and autocomplete functionality.

8. Recommendation Service

Overview:
- Provides personalized business and review recommendations for users.
Features:
- Uses machine learning models to analyze user behavior and preferences.

9. Notification Service

Overview:
- Sends updates and alerts to users and business owners about reviews, responses, and flagged content.
Features:
- Push notifications, emails, and real-time alerts.

10. Moderation Service

Overview:
- Handles flagged reviews and photos for inappropriate content.
Features:
- Enables admins to review and act on flagged content.

11. Analytics and Reporting Service

Overview:
- Aggregates user interaction data and generates insights for business owners and admins.
Features:
- Tracks views, clicks, and reviews; generates platform-wide statistics.

12. Search Index Database

Overview:
- Stores indexed data for fast text and geospatial searches.
Features:
- Optimized for proximity-based and relevance-based queries.

13. Offline Access Service

Overview:
- Allows users to download and access business information offline.
Features:
- Provides cached business details, reviews, and photos.

14. Data Pipeline

Overview:
- Processes and aggregates data for analytics and machine learning.
Features:
- Handles real-time data ingestion and batch processing.

15. Load Balancer

Overview:
- Distributes incoming traffic across servers to ensure high availability and performance.
Features:
- Fault tolerance and traffic management during peak loads.

16. Monitoring and Logging Service

Overview:
- Tracks system performance and logs user activities for debugging and insights.
Features:
- Alerts for system health issues and detailed activity logs.

flowchart TD
    Client[Client Interface] --> Gateway{API Gateway}
    Gateway --> Auth[Authentication Service]
    Gateway --> Search[Search Service]
    Gateway --> Review[Review Management Service]
    Gateway --> Photo[Photo Management Service]
    Gateway --> Notification[Notification Service]
    Gateway --> Business[Business Management Service]
    Gateway --> Moderation[Moderation Service]
    Gateway --> Analytics[Analytics Service]
    Search --> SearchDB[Search Index Database]
    Review --> ReviewDB[Review Database]
    Photo --> PhotoDB[Photo Metadata Database]
    Photo --> ObjectStorage[Photo Storage S3]
    Notification --> NotificationQueue[Notification Queue]
    Business --> BusinessDB[Business Database]
    Moderation --> ModerationQueue[Moderation Database]
    Auth --> UserDB[User Database]
    Analytics --> AnalyticsDB[Analytics Database]
    Review --> SearchDB
    Business --> SearchDB

Request flows

1. User Registration

User Interface:
- User inputs name, email, and password on the registration page.
API Gateway:
- Routes the request to the User Management Service.
User Management Service:
- Validates input and checks for duplicate email.
- Hashes the password and creates a new user entry in the User Database.
Database Interaction:
- Inserts user details into the User Database.
Response:
- Returns a success message to the user.

2. Business Search

User Interface:
- User enters search terms and filters on the search bar.
API Gateway:
- Routes the request to the Search Service.
Search Service:
- Queries the Search Index Database for matching businesses.
- Applies filters like category, location, and rating.
Database Interaction:
- Fetches relevant business data from the Business Database.
Response:
- Sends the list of matching businesses back to the user.

3. Submit a Review

User Interface:
- User submits a review for a specific business.
API Gateway:
- Routes the request to the Review Management Service.
Review Management Service:
- Validates the review content and user authentication.
- Saves the review in the Review Database.
Database Interaction:
- Updates the Search Index with the new review.
- Updates aggregated ratings for the business in the Business Database.
Notification Service:
- Sends a notification to the business owner about the new review.
Response:
- Confirms the review submission to the user.

4. Upload a Photo

User Interface:
- User selects and uploads a photo for a business.
API Gateway:
- Routes the request to the Photo Management Service.
Photo Management Service:
- Processes and stores the photo in Object Storage (e.g., AWS S3).
- Saves metadata (e.g., uploader_id, business_id, URL) in the Photo Database.
Database Interaction:
- Links the photo to the corresponding business in the database.
Response:
- Confirms the upload and displays the photo to the user.

5. Business Claim by Owner

User Interface:
- Business owner submits a claim request for their business.
API Gateway:
- Routes the request to the Business Management Service.
Business Management Service:
- Validates the owner’s identity.
- Updates the ownership status in the Business Database.
Notification Service:
- Notifies the admin team for verification, if required.
Response:
- Confirms the claim request submission to the owner.

6. Notification Retrieval

User Interface:
- User checks notifications via the app or website.
API Gateway:
- Routes the request to the Notification Service.
Notification Service:
- Fetches unread notifications from the Notification Database.
Response:
- Displays notifications to the user.

7. Flagging Inappropriate Content

User Interface:
- User flags a review or photo as inappropriate.
API Gateway:
- Routes the request to the Moderation Service.
Moderation Service:
- Saves the flagged content in the Moderation Queue Database.
Notification:
- Notifies the admin team for review.
Response:
- Confirms the flag submission to the user.

8. Analytics Retrieval

User Interface:
- Business owner or admin views analytics.
API Gateway:
- Routes the request to the Analytics Service.
Analytics Service:
- Fetches data from the Analytics Database.
Response:
- Displays detailed insights to the user.

9. Geolocation-Based Search

User Interface:
- User opts to search nearby businesses.
API Gateway:
- Routes the request to the Search Service.
Search Service:
- Queries the Search Index for businesses near the user’s geolocation.
Database Interaction:
- Retrieves business details from the Business Database.
Response:
- Displays a map with nearby businesses.

sequenceDiagram
    User->>+API Gateway: Submit Request (e.g., Search Business)
    API Gateway->>+Authentication Service: Validate User Token
    Authentication Service-->>-API Gateway: Token Validated
    API Gateway->>+Search Service: Process Search Query
    Search Service->>+Search Index Database: Fetch Relevant Businesses
    Search Index Database-->>-Search Service: Search Results
    Search Service->>+Business Database: Fetch Business Details
    Business Database-->>-Search Service: Business Information
    Search Service-->>-API Gateway: Search Results with Business Data
    API Gateway-->>-User: Response Sent to User

    User->>+API Gateway: Submit a Review
    API Gateway->>+Review Service: Validate and Process Review
    Review Service->>+Review Database: Save Review
    Review Database-->>-Review Service: Review Saved
    Review Service->>+Search Index Database: Update Search Index with Review
    Search Index Database-->>-Review Service: Index Updated
    Review Service->>+Notification Service: Notify Business Owner
    Notification Service->>+Notification Queue: Queue Notification
    Notification Queue-->>-Notification Service: Notification Sent
    Review Service-->>-API Gateway: Review Submission Confirmed
    API Gateway-->>-User: Response Sent to User

    User->>+API Gateway: Upload a Photo
    API Gateway->>+Photo Service: Process and Store Photo
    Photo Service->>+Object Storage: Save Photo
    Object Storage-->>-Photo Service: Photo Saved
    Photo Service->>+Photo Metadata Database: Save Photo Metadata
    Photo Metadata Database-->>-Photo Service: Metadata Saved
    Photo Service-->>-API Gateway: Photo Upload Confirmed
    API Gateway-->>-User: Response Sent to User

Detailed component design

1. Search Service

1. End-to-End Working

Accepts user queries via the API Gateway.
Parses query parameters (keywords, filters like location or category).
Queries the Search Index Database (Elasticsearch) for relevant matches using full-text and geospatial search.
Applies filters (e.g., category, proximity) and ranks results based on relevance.
Returns the results to the user.

2. Data Structures and Algorithms

Inverted Index: Maps keywords to document IDs for efficient text search.
R-Trees/Geohashing: For spatial indexing to handle proximity-based queries.
TF-IDF or BM25: Scoring algorithms to rank search results by relevance.
Trie Structure: For efficient autocomplete suggestions.

3. Handling Peak Traffic (Scaling)

Sharded Index: Divides search data across nodes by region or category to distribute load.
Caching: Frequently searched queries are cached in Redis for faster responses.
Horizontal Scaling: Additional Elasticsearch nodes are deployed to handle increased query volume.

4. Edge Cases and Handling

Case 1: Typo in Search Query:
- Handling: Implements fuzzy search with Levenshtein distance to suggest corrections.
Case 2: No Results Found:
- Handling: Suggests popular businesses or categories as fallback.
Case 3: High Query Volume:
- Handling: Rate limits users during extreme surges and prioritizes logged-in users.

2. Review Management Service

1. End-to-End Working

Accepts review submissions via the API Gateway.
Validates review content and user authentication.
Stores reviews in the Review Database (MongoDB).
Updates the Search Index with the review for improved business visibility.
Sends notifications to business owners and relevant users.

2. Data Structures and Algorithms

Document Store: MongoDB’s flexible schema for storing diverse review content.
TTL Indexes: Automatically deletes flagged or temporary reviews after a set period.
Aggregation Pipelines: Efficiently calculates business ratings and review counts.

3. Handling Peak Traffic (Scaling)

Partitioned Collections: Shards reviews by business ID to distribute writes.
Write Queues: Temporarily queues reviews for delayed processing during heavy loads.
Horizontal Scaling: Adds MongoDB nodes to scale read and write capacity.

4. Edge Cases and Handling

Case 1: Duplicate Reviews:
- Handling: Enforces uniqueness by combining user ID and business ID.
Case 2: Profanity or Inappropriate Content:
- Handling: Filters reviews with text-analysis models and flags inappropriate ones.
Case 3: Review Flooding:
- Handling: Rate limits review submissions to prevent spam.

3. Photo Management Service

1. End-to-End Working

Processes photo uploads from users.
Stores photos in Object Storage (AWS S3/Google Cloud Storage).
Saves metadata (e.g., uploader ID, business ID) in the Photo Database.
Links photos to the corresponding business profile.

2. Data Structures and Algorithms

Object Metadata: Stored in relational format for efficient indexing and retrieval.
Content Delivery Networks (CDN): Ensures fast photo delivery to end-users.
Chunked Uploads: Splits large files into smaller parts for efficient uploads.

3. Handling Peak Traffic (Scaling)

CDN Integration: Caches frequently accessed photos at the edge for low-latency delivery.
Object Storage Partitioning: Distributes photos across multiple storage buckets.
Upload Queueing: Handles burst traffic by queueing uploads during surges.

4. Edge Cases and Handling

Case 1: Large File Uploads:
- Handling: Implements chunked uploads and retries for network failures.
Case 2: Duplicate Photo Uploads:
- Handling: Uses hash-based deduplication to avoid redundant storage.
Case 3: Photo Abuse (e.g., offensive content):
- Handling: Integrates AI-based moderation tools to flag inappropriate images.

4. Notification Service

1. End-to-End Working

Receives events like new reviews or flagged content.
Queues notifications in the Notification Queue.
Delivers notifications to users via push notifications or email.
Updates notification statuses in the Notification Database.

2. Data Structures and Algorithms

Priority Queues: Ensures high-priority notifications (e.g., flagged content) are delivered first.
Redis Pub/Sub: Real-time delivery of notifications.
Event-Driven Architecture: Processes notifications asynchronously for scalability.

3. Handling Peak Traffic (Scaling)

Message Queues: Uses RabbitMQ/Kafka to buffer notifications during spikes.
Parallel Processing: Processes notification batches with worker nodes.
Fallback Mechanisms: Switches to delayed email notifications during service outages.

4. Edge Cases and Handling

Case 1: Undelivered Notifications:
- Handling: Implements retries with exponential backoff.
Case 2: Notification Flooding:
- Handling: Groups multiple notifications into a single digest for the user.
Case 3: Failed Delivery Channels:
- Handling: Switches between push, SMS, or email channels based on availability.

5. Business Management Service

1. End-to-End Working

Handles CRUD operations for business listings.
Allows business owners to claim listings after verification.
Updates business information in the Business Database and Search Index.

2. Data Structures and Algorithms

Relational Tables: Efficiently store structured data like business details.
Verification Workflow: Processes claims with step-by-step verification checks.

3. Handling Peak Traffic (Scaling)

Read Replicas: Serves high read traffic from replicas to offload the primary database.
Async Index Updates: Processes search index updates in batches to reduce load.
Horizontal Scaling: Scales business management microservices to handle concurrent updates.

4. Edge Cases and Handling

Case 1: Duplicate Business Listings:
- Handling: Merges listings with matching metadata.
Case 2: Fake Business Claims:
- Handling: Requires ownership proofs (e.g., utility bills or government-issued IDs).
Case 3: Large Updates (e.g., bulk edits):
- Handling: Processes updates in smaller batches to avoid database overload.

Trade offs/Tech choices

MongoDB for Reviews:

Trade-Off: Flexibility for diverse review structures but lacks strong consistency.
Reason: Reviews are dynamic and vary in content; MongoDB's schema flexibility handles this efficiently.

Elasticsearch for Search:

Trade-Off: High resource usage but provides fast and accurate full-text and geospatial search.
Reason: Optimized for real-time search and filtering across large datasets.

AWS S3 for Photo Storage:

Trade-Off: Higher latency compared to local storage but highly scalable and cost-effective for large volumes of photos.
Reason: Ensures durability and easy integration with CDNs for global delivery.

PostgreSQL for Users:

Trade-Off: More complex scaling compared to NoSQL, but provides strong consistency.
Reason: Relational structure fits well with user authentication and profile management.

Event-Driven Notifications:

Trade-Off: Adds complexity with message queues but decouples services for scalability and fault tolerance.
Reason: Handles high notification volumes asynchronously for better performance.

Failure scenarios/bottlenecks

Search Index Overload:

Issue: High query volume slows down Elasticsearch.
Mitigation: Implement caching for frequent queries and shard the index.

Photo Storage Latency:

Issue: Slow uploads or retrievals during traffic surges.
Mitigation: Use CDNs and chunked uploads for scalability.

Database Overload:

Issue: High read/write traffic on relational databases.
Mitigation: Use read replicas, query optimization, and caching.

Notification Delays:

Issue: Message queues back up during peaks.
Mitigation: Scale workers and prioritize notifications.

Review Spam:

Issue: Excessive or inappropriate reviews overwhelm the system.
Mitigation: Use rate limiting and automated moderation tools.

Service Downtime:

Issue: API Gateway or key services become unavailable.
Mitigation: Use load balancers, failover servers, and health checks.

Flagged Content Abuse:

Issue: Users maliciously flag valid reviews or photos.
Mitigation: Implement user reputation scoring and manual moderation.

Scaling Bottlenecks:

Issue: Inefficient horizontal scaling under sudden spikes.
Mitigation: Pre-scale resources during predicted high traffic.

Future improvements

Enhanced Search Optimization:

Improvement: Use ML-based ranking for personalized search results.
Mitigation: Reduces search index bottlenecks with smarter query handling.

AI-Powered Moderation:

Improvement: Deploy AI models for review and photo moderation.
Mitigation: Minimizes flagged content abuse and reduces manual workload.

Real-Time Analytics:

Improvement: Introduce real-time pipelines for instant business insights.
Mitigation: Handles database overload by offloading analytics.

Auto-Scaling for Peak Traffic:

Improvement: Implement predictive auto-scaling for all services.
Mitigation: Prepares the system for sudden traffic spikes.

Enhanced Caching Strategy:

Improvement: Expand caching for popular searches, reviews, and photos.
Mitigation: Alleviates search index and database load during peaks.

Improved Notification Handling:

Improvement: Group similar notifications and introduce digest alerts.
Mitigation: Prevents queue backlogs and reduces delivery delays.

Offline Capabilities:

Improvement: Allow users to download more robust offline data.
Mitigation: Reduces reliance on real-time data during outages.

Solutions

alchemy1135 - 03/15/2024

1

quest3775 - 03/12/2024

1

nectar4678 - 03/11/2024

2

utopia4715 - 05/25/2024

1

iridescent_luminous693 - 01/02/2025

0