My Solution for Design a Platform Like Reddit with Score: 8/10

by iridescent_luminous693

System requirements


Functional Requirements

Core Functionalities:

  1. User Management:
    • Allow users to create accounts, log in, and manage profiles.
    • Provide role-based access for moderators and administrators.
  2. Content Creation and Interaction:
    • Users can submit posts (text or links) and upload media (images/videos).
    • Enable upvotes, downvotes, and comments on posts.
    • Allow users to create, join, and participate in communities (subreddits).
  3. Community Management:
    • Allow users to create and moderate subreddits.
    • Support customizable subreddit rules and styles.
  4. Search and Discovery:
    • Search for posts, comments, and subreddits by keywords.
    • Provide personalized content recommendations.
  5. Moderation and Reporting:
    • Enable reporting of inappropriate content or users.
    • Allow moderators to remove posts and ban users.
  6. Real-Time Notifications:
    • Notify users about new comments, replies, and messages.

Non-Functional Requirements

  1. Scalability:
    • Handle millions of concurrent users and thousands of active communities.
  2. Availability:
    • Ensure 99.99% uptime to maintain continuous access.
  3. Performance:
    • Load pages and search results within milliseconds.
    • Support real-time voting and comment updates.
  4. Security:
    • Protect user data with encryption and secure authentication.
    • Prevent spam and bot activity.
  5. Extensibility:
    • Support integration with third-party APIs (e.g., content moderation tools).
  6. Data Integrity:
    • Ensure consistency in vote counts, comment threads, and user actions.




Capacity estimation

Estimate the scale of the system you are going to design...


Assumptions:

  1. Users:
    • Total registered users: 100 million.
    • Daily active users (DAUs): 20 million (20%).
  2. Posts and Comments:
    • Daily posts: 1 million.
    • Daily comments: 10 million.
    • Average post size: 1 KB (text) or 5 MB (media).
    • Average comment size: 500 bytes.
  3. Votes:
    • Daily upvotes/downvotes: 100 million.
  4. Storage:
    • Average post size (text + metadata): 1 KB.
    • Daily post storage: 1 million×1 KB=1 GB/day1 \, \text{million} \times 1 \, \text{KB} = 1 \, \text{GB/day}1million×1KB=1GB/day.
    • Annual post storage: 1 GB/day×365=365 GB/year1 \, \text{GB/day} \times 365 = 365 \, \text{GB/year}1GB/day×365=365GB/year.




API design

Define what APIs are expected from the system...


1. User Management APIs

  • POST /api/users/register: Create a new user account.
  • POST /api/users/login: Authenticate user credentials.
  • GET /api/users/{user_id}: Fetch user profile details.

2. Post Management APIs

  • POST /api/posts/create: Submit a new post.
  • GET /api/posts/{post_id}: Retrieve a specific post.
  • PUT /api/posts/{post_id}/vote: Upvote or downvote a post.
  • DELETE /api/posts/{post_id}: Remove a post.

3. Comment Management APIs

  • POST /api/comments/create: Add a comment to a post.
  • GET /api/comments/{comment_id}: Retrieve a specific comment.
  • PUT /api/comments/{comment_id}/vote: Upvote or downvote a comment.

4. Subreddit Management APIs

  • POST /api/subreddits/create: Create a new subreddit.
  • GET /api/subreddits/{subreddit_id}: Retrieve subreddit details.
  • POST /api/subreddits/{subreddit_id}/moderators: Assign moderators to a subreddit.

5. Search and Discovery APIs

  • GET /api/search: Search posts, comments, or subreddits.
  • GET /api/recommendations: Fetch personalized content recommendations.

6. Notification APIs

  • GET /api/notifications: Retrieve user notifications.
  • POST /api/notifications/mark_as_read: Mark notifications as read.




Database design

Defining the system data model early on will clarify how data will flow among different components of the system. Also you could draw an ER diagram using the diagramming tool to enhance your design...


1. User Database

  • Schema Details:
    • Table Name: Users
      • user_id (Primary Key): Unique identifier for each user.
      • username: User’s chosen display name.
      • email: User’s email address.
      • password_hash: Hashed password.
      • created_at: Timestamp of account creation.
  • Purpose:
    • Store user details and authentication information.
  • Tech Used:
    • Relational Database (e.g., PostgreSQL).
  • Tradeoff:
    • Pros: Strong consistency for user authentication and profile updates.
    • Cons: Requires sharding to scale with a large number of users.

2. Post Database

  • Schema Details:
    • Table Name: Posts
      • post_id (Primary Key): Unique identifier for each post.
      • user_id (Foreign Key): Associated user ID.
      • subreddit_id (Foreign Key): Associated subreddit ID.
      • content: Text content or media URL.
      • votes: Upvote and downvote counts.
      • created_at: Timestamp of post creation.
  • Purpose:
    • Store post details, including metadata and content.
  • Tech Used:
    • NoSQL Database (e.g., MongoDB).
  • Tradeoff:
    • Pros: Scalable for high write throughput and flexible schema for varying post types.
    • Cons: Complex queries for relational operations require additional processing.

3. Comment Database

  • Schema Details:
    • Table Name: Comments
      • comment_id (Primary Key): Unique identifier for each comment.
      • post_id (Foreign Key): Associated post ID.
      • user_id (Foreign Key): Associated user ID.
      • content: Text content of the comment.
      • votes: Upvote and downvote counts.
      • created_at: Timestamp of comment creation.
  • Purpose:
    • Manage threaded discussions for posts.
  • Tech Used:
    • Relational Database (e.g., MySQL).
  • Tradeoff:
    • Pros: Ensures consistency for threaded discussions.
    • Cons: May require indexing for efficient retrieval in deeply nested threads.

4. Subreddit Database

  • Schema Details:
    • Table Name: Subreddits
      • subreddit_id (Primary Key): Unique identifier for each subreddit.
      • name: Name of the subreddit.
      • description: Description of the subreddit.
      • created_at: Timestamp of subreddit creation.
  • Purpose:
    • Manage subreddit details and metadata.
  • Tech Used:
    • Relational Database (e.g., PostgreSQL).
  • Tradeoff:
    • Pros: Supports complex queries for subreddit management.
    • Cons: Requires sharding to handle large-scale subreddit data.

5. Notifications Database

  • Schema Details:
    • Table Name: Notifications
      • notification_id (Primary Key): Unique identifier for each notification.
      • user_id (Foreign Key): Associated user ID.
      • type: Type of notification (e.g., new comment, upvote).
      • content: Notification details.
      • created_at: Timestamp of notification creation.
  • Purpose:
    • Track and deliver user notifications.
  • Tech Used:
    • NoSQL Database (e.g., DynamoDB).
  • Tradeoff:
    • Pros: High scalability and low-latency access for real-time notifications.
    • Cons: Limited querying capabilities for complex notification analytics.

6. Search Index

  • Schema Details:
    • Index Name: SearchIndex
      • document_id: Identifier for posts, comments, or subreddits.
      • type: Document type (e.g., post, comment, subreddit).
      • content: Indexed content for search.
      • metadata: Associated metadata (e.g., tags, votes).
  • Purpose:
    • Enable fast and relevant search and discovery.
  • Tech Used:
    • Search Engine (e.g., Elasticsearch).
  • Tradeoff:
    • Pros: Optimized for full-text search and relevance ranking.
    • Cons: Requires frequent indexing updates to maintain data freshness.




High-level design

You should identify enough components that are needed to solve the actual problem from end to end. Also remember to draw a block diagram using the diagramming tool to augment your design. If you are unfamiliar with the tool, you can simply describe your design to the chat bot and ask it to generate a starter diagram for you to modify...


1. User Management Service

Overview:

Manages user accounts, authentication, and roles. Provides functionalities for registration, login, and managing user profiles.

Responsibilities:

  • Handle user registration and authentication.
  • Manage user profiles, including avatar, bio, and settings.
  • Assign roles such as moderators or administrators for subreddits.

2. Subreddit Management Service

Overview:

Handles subreddit creation, configuration, and moderation.

Responsibilities:

  • Enable users to create and customize subreddits.
  • Manage subreddit-specific rules, themes, and moderators.
  • Handle subreddit access control (public or private).

3. Post and Comment Service

Overview:

Manages user-generated content, including posts and threaded comments.

Responsibilities:

  • Allow users to create, edit, and delete posts.
  • Support upvotes, downvotes, and threaded discussions.
  • Provide APIs for fetching post and comment details efficiently.

4. Voting Service

Overview:

Tracks upvotes and downvotes for posts and comments.

Responsibilities:

  • Maintain vote counts for posts and comments.
  • Ensure idempotent voting to prevent duplicate votes from a user.
  • Update ranking scores for content based on votes.

5. Search and Discovery Service

Overview:

Enables users to search for posts, comments, and subreddits, and provides personalized recommendations.

Responsibilities:

  • Index and search for posts, comments, and subreddits.
  • Provide trending posts and personalized content recommendations.
  • Enable users to discover new subreddits based on interests.

6. Notification Service

Overview:

Manages notifications for user interactions, such as comments, replies, and private messages.

Responsibilities:

  • Notify users about new comments, upvotes, or replies.
  • Handle subscription-based notifications for subreddits or threads.
  • Provide APIs to retrieve and mark notifications as read.

7. Moderation Service

Overview:

Supports community moderation by providing tools for reporting, reviewing, and removing inappropriate content.

Responsibilities:

  • Enable users to report posts, comments, or users.
  • Allow moderators to remove content and ban users.
  • Log moderation actions for audit purposes.

8. Analytics and Monitoring Service

Overview:

Tracks platform activity and generates insights for admins and moderators.

Responsibilities:

  • Monitor user activity and engagement metrics.
  • Provide dashboards for subreddit analytics (e.g., most active posts).
  • Generate alerts for unusual activity (e.g., spam).




Request flows

Explain how the request flows from end to end in your high level design. Also you could draw a sequence diagram using the diagramming tool to enhance your explanation...


1. User Registration

Objective: Create a new user account.

Steps:

  1. API Gateway:
    • Receives a POST /api/users/register request with user details.
    • Validates the input and forwards it to the User Management Service.
  2. User Management Service:
    • Verifies that the username and email are unique.
    • Hashes the password for secure storage.
    • Creates a new user record in the User Database.
  3. Response:
    • Returns a success message with the user ID.

2. Create a Subreddit

Objective: Allow a user to create a new subreddit.

Steps:

  1. API Gateway:
    • Receives a POST /api/subreddits/create request with subreddit details.
    • Authenticates the user and forwards the request to the Subreddit Management Service.
  2. Subreddit Management Service:
    • Validates the subreddit name for uniqueness.
    • Creates a new subreddit record in the Subreddit Database.
    • Assigns the requesting user as the subreddit’s moderator.
  3. Response:
    • Confirms subreddit creation and returns the subreddit ID.

3. Submit a Post

Objective: Submit a new post in a subreddit.

Steps:

  1. API Gateway:
    • Receives a POST /api/posts/create request with the post details.
    • Authenticates the user and forwards the request to the Post and Comment Service.
  2. Post and Comment Service:
    • Validates the subreddit and user permissions.
    • Creates a new post record in the Post Database.
  3. Notification Service:
    • Notifies subreddit subscribers about the new post.
  4. Response:
    • Confirms the post submission and returns the post ID.

4. Upvote a Post

Objective: Allow a user to upvote a post.

Steps:

  1. API Gateway:
    • Receives a PUT /api/posts/{post_id}/vote request with the vote action.
    • Authenticates the user and forwards the request to the Voting Service.
  2. Voting Service:
    • Validates the vote action and checks for idempotency.
    • Updates the vote count in the Post Database.
  3. Search and Discovery Service:
    • Updates the ranking score of the post in the search index.
  4. Response:
    • Confirms the vote action and returns the updated vote count.

5. Search for Posts

Objective: Search for posts matching a query.

Steps:

  1. API Gateway:
    • Receives a GET /api/search request with query parameters.
    • Forwards the request to the Search and Discovery Service.
  2. Search and Discovery Service:
    • Queries the Search Index for matching posts, comments, or subreddits.
    • Applies relevance ranking based on vote counts and user preferences.
  3. Response:
    • Returns a list of matching results with metadata.

6. Notify a User of a Comment

Objective: Notify a user when someone comments on their post.

Steps:

  1. API Gateway:
    • Receives a POST /api/comments/create request with the comment details.
    • Authenticates the user and forwards the request to the Post and Comment Service.
  2. Post and Comment Service:
    • Validates the post ID and creates a comment record in the Comment Database.
  3. Notification Service:
    • Sends a notification to the post’s author about the new comment.
  4. Response:
    • Confirms the comment submission and returns the comment ID.

7. Report a Post

Objective: Report inappropriate content for review.

Steps:

  1. API Gateway:
    • Receives a POST /api/posts/{post_id}/report request.
    • Authenticates the user and forwards the request to the Moderation Service.
  2. Moderation Service:
    • Logs the report and marks the post for review.
    • Notifies the subreddit moderators.
  3. Response:
    • Confirms the report submission.




Detailed component design

Dig deeper into 2-3 components and explain in detail how they work. For example, how well does each component scale? Any relevant algorithm or data structure you like to use for a component? Also you could draw a diagram using the diagramming tool to enhance your design...



1. User Management Service

End-to-End Working:

The User Management Service manages user registration, authentication, and profile settings. When a user registers, the service validates input, hashes passwords using algorithms like bcrypt, and stores user details in the database. Authentication involves validating credentials, generating session tokens (e.g., JWT), and maintaining session metadata. Role-based access controls (RBAC) ensure user permissions for specific actions (e.g., moderating subreddits).

Communication:

  • Protocols Used:
    • HTTPS: Ensures secure transmission of sensitive data like passwords.
    • REST APIs: Handles registration, login, and profile updates.
  • Inter-Service Communication:
    • Notifies the Subreddit Management Service for role assignments (e.g., moderator).
    • Sends user activity logs to the Analytics Service for tracking.

Data Structures and Algorithms:

  • Hash Maps for Session Management:
    • Cache active user sessions in Redis for quick lookup.
  • Password Hashing:
    • Uses bcrypt or Argon2 for secure, computationally expensive password storage.
  • RBAC Matrix:
    • A two-dimensional matrix maps roles to permissions, ensuring efficient access control checks.

Implementation Example (Session Token Generation):

python Copy code import jwt from datetime import datetime, timedelta def generate_token(user_id): payload = { "user_id": user_id, "exp": datetime.utcnow() + timedelta(hours=1) } return jwt.encode(payload, "secret_key", algorithm="HS256")

Scaling for Peak Traffic:

  • Horizontal Scaling:
    • Deploy multiple stateless instances of the service behind a load balancer.
  • Caching:
    • Cache user session tokens in Redis to reduce database load.
  • Rate Limiting:
    • Apply rate limiting to prevent abuse (e.g., brute-force login attempts).

Edge Cases:

  • Duplicate Registrations:
    • Enforce unique constraints on email and username fields in the database.
  • Token Expiry:
    • Implement token refresh mechanisms for seamless user experiences.
  • Forgotten Passwords:
    • Generate secure, time-limited links for password recovery.

2. Subreddit Management Service

End-to-End Working:

The Subreddit Management Service handles subreddit creation, configuration, and moderation. When a user creates a subreddit, the service validates the name, assigns default settings, and stores metadata in the database. Moderators can update rules and assign roles, ensuring subreddit-specific governance.

Communication:

  • Protocols Used:
    • HTTPS: Handles secure communication for subreddit creation and updates.
    • REST APIs: Interfaces with the Post Service to fetch subreddit-specific posts.
  • Inter-Service Communication:
    • Retrieves user roles from the User Management Service to validate permissions.
    • Sends subreddit activity data to the Analytics Service.

Data Structures and Algorithms:

  • Trie for Subreddit Name Search:
    • Efficiently handles autocomplete and search suggestions for subreddit names.
  • Role-Based Access Control (RBAC):
    • Uses hash maps to manage moderator and user permissions at the subreddit level.

Implementation Example (RBAC for Moderation):

python Copy code class RBAC: def __init__(self): self.roles = {"admin": ["add_mod", "remove_post"], "mod": ["remove_post"]} def has_permission(self, role, action): return action in self.roles.get(role, [])

Scaling for Peak Traffic:

  • Database Sharding:
    • Shard subreddit data based on subreddit ID or category for efficient querying.
  • Cache Metadata:
    • Cache frequently accessed subreddit settings in Redis or Memcached.

Edge Cases:

  • Subreddit Name Conflicts:
    • Enforce unique constraints and suggest alternatives for conflicting names.
  • Mismanagement by Moderators:
    • Implement escalation mechanisms for appeals to admins.

3. Post and Comment Service

End-to-End Working:

The Post and Comment Service manages user-generated content, including posts and threaded comments. When a post is submitted, it validates the subreddit ID, processes content (e.g., sanitizing HTML), and stores it in the database. Threaded comments are represented using parent-child relationships.

Communication:

  • Protocols Used:
    • REST APIs: Handles post and comment CRUD operations.
    • WebSockets: Streams real-time updates for comments and votes.
  • Inter-Service Communication:
    • Notifies the Search Service to index new posts and comments.
    • Sends vote updates to the Voting Service.

Data Structures and Algorithms:

  • Adjacency List for Comments:
    • Represents threaded discussions, with each comment node pointing to its parent.
  • Ranking Algorithm:
    • Uses weighted formulas (e.g., Hotness algorithm) to rank posts based on votes and time.

Implementation Example (Hotness Algorithm):

python Copy code import math from datetime import datetime def calculate_hotness(score, created_at): order = math.log(max(abs(score), 1), 10) seconds = (created_at - datetime(1970, 1, 1)).total_seconds() return order + seconds / 45000

Scaling for Peak Traffic:

  • Write Optimization:
    • Use NoSQL databases like MongoDB for fast writes.
  • Asynchronous Processing:
    • Offload heavy tasks (e.g., media processing) to background workers.

Edge Cases:

  • Deeply Nested Threads:
    • Limit nesting depth and flatten threads for better performance.
  • Spam Posts:
    • Use AI-based moderation tools to flag or auto-remove spam.

4. Voting Service

End-to-End Working:

The Voting Service tracks upvotes and downvotes for posts and comments. It ensures idempotency (one vote per user per item) and updates content ranking in real time.

Communication:

  • Protocols Used:
    • REST APIs: Processes vote actions.
    • gRPC: Communicates with the Post Service to update ranking.
  • Inter-Service Communication:
    • Sends vote counts to the Analytics Service.
    • Updates the Search Index with new scores.

Data Structures and Algorithms:

  • Hash Maps for Vote Tracking:
    • Tracks user-vote relationships to prevent duplicate votes.
  • Priority Queue for Ranking:
    • Updates content ranking efficiently using a heap.

Implementation Example (Vote Tracking):

python Copy code class VoteTracker: def __init__(self): self.votes = {} def cast_vote(self, user_id, post_id, vote): self.votes[(user_id, post_id)] = vote

Scaling for Peak Traffic:

  • Event-Driven Architecture:
    • Use Kafka or RabbitMQ to process vote events asynchronously.
  • Distributed Databases:
    • Partition vote data by post or subreddit ID.

Edge Cases:

  • Vote Manipulation:
    • Detect and block vote brigades using anomaly detection.
  • Idempotency Issues:
    • Store vote actions with unique identifiers to prevent duplicate processing.

5. Search and Discovery Service

End-to-End Working:

The Search and Discovery Service indexes posts, comments, and subreddits for fast retrieval. It uses Elasticsearch for full-text search and relevance ranking. Personalized recommendations are generated using collaborative filtering.

Communication:

  • Protocols Used:
    • REST APIs: Handles search queries.
    • gRPC: Fetches metadata from the Post Service for indexing.
  • Inter-Service Communication:
    • Sends personalized recommendations to the Notification Service.

Data Structures and Algorithms:

  • Inverted Index:
    • Maps keywords to document IDs for efficient full-text search.
  • Collaborative Filtering:
    • Recommends content based on user behavior similarity.

Implementation Example (Inverted Index Search):

python Copy code class InvertedIndex: def __init__(self): self.index = {} def add_document(self, doc_id, terms): for term in terms: self.index.setdefault(term, []).append(doc_id)

Scaling for Peak Traffic:

  • Sharding:
    • Distribute the index across multiple nodes based on data type (e.g., posts, comments).
  • Query Caching:
    • Cache frequent search queries for faster responses.

Edge Cases:

  • Data Freshness:
    • Implement near-real-time indexing for new content.
  • Query Overload:
    • Apply rate limiting and query optimization techniques.



Trade offs/Tech choices

Explain any trade offs you have made and why you made certain tech choices...



Microservices Architecture:

  • Trade-off: Increased complexity in managing inter-service communication and deployments.
  • Reason: Allows independent scaling, fault isolation, and easier addition of new features.

NoSQL for Posts and Comments:

  • Trade-off: Limited support for complex relational queries.
  • Reason: Provides high write throughput and flexible schema for varied content types.

Redis for Caching:

  • Trade-off: Requires careful cache eviction policies to avoid stale data.
  • Reason: Reduces load on primary databases and improves read performance.

Inverted Index for Search:

  • Trade-off: Requires frequent re-indexing to maintain freshness.
  • Reason: Enables fast and efficient full-text search capabilities.



Failure scenarios/bottlenecks

Try to discuss as many failure scenarios/bottlenecks as possible.


Content Moderation Overload:

  • Issue: High volume of reported content may overwhelm moderators.
  • Mitigation: Use AI-based moderation to pre-filter flagged content.

Vote Manipulation:

  • Issue: Coordinated vote brigades can artificially promote/demote content.
  • Mitigation: Implement rate limiting and anomaly detection algorithms.

High Query Load on Search:

  • Issue: Search service may slow down during peak traffic.
  • Mitigation: Use sharding for distributed search indices and cache frequent queries.

Database Overload:

  • Issue: High write volumes for votes, posts, and comments may strain the database.
  • Mitigation: Partition databases by subreddit or user ID and use asynchronous processing for non-critical tasks.

Cache Inconsistency:

  • Issue: Stale data in Redis may lead to outdated or incorrect results.
  • Mitigation: Implement cache expiration policies and cache invalidation on updates.




Future improvements

What are some future improvements you would make? How would you mitigate the failure scenario(s) you described above?


Advanced Recommendation System:

  • Improvement: Use deep learning models to personalize content recommendations further.
  • Mitigation: Leverage embeddings and collaborative filtering with scalable ML pipelines.

Real-Time Content Moderation:

  • Improvement: Integrate real-time AI-based content moderation tools.
  • Mitigation: Reduce moderator workload and quickly address inappropriate content.

Geographic Data Replication:

  • Improvement: Deploy regional replicas of databases for reduced latency in global traffic.
  • Mitigation: Use eventual consistency models for non-critical data.

Dynamic Autoscaling:

  • Improvement: Predict traffic spikes using AI and proactively scale infrastructure.
  • Mitigation: Prevent system slowdowns during peak activity.

Robust Search Optimizations:

  • Improvement: Implement query rewriting and smarter ranking algorithms.
  • Mitigation: Improve search accuracy and speed while reducing resource usage.