Online Chess Game System Design

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Questions and Answers

In a chess game system designed for 100 million MAU, which component is MOST critical for maintaining smooth gameplay with minimal delay?

  • Persistent Layer (Database)
  • Game Engine with Move Validation
  • WebSocket Servers for Real-time Communication (correct)
  • Application Servers handling User Logins

The chess game system should allow players to undo a move if both players agree it was a mistake.

False (B)

What is the expected latency of the online chess game system to ensure smooth gameplay and response time, as specified in the nonfunctional requirements?

100 ms

In the high-level design of the chess game, the component responsible for managing the life cycle of game engine instances and distributing load among them is known as the ______.

<p>Game Engine Manager</p> Signup and view all the answers

Match the architectural components of the chess game system with their respective responsibilities:

<p>API Gateways = Entry point for all client requests, handling routing and authentication. Load Balancers = Distribute incoming network traffic across multiple servers to ensure no single server is overwhelmed. Game Engine = Validates moves, manages the game state, and enforces the rules of chess. Persistent Layer = Stores all game-related data, including game states, player moves, and statistics.</p> Signup and view all the answers

Which of the following is NOT a functional requirement for the chess game system?

<p>Maintaining a latency of less than 100 ms. (A)</p> Signup and view all the answers

The primary purpose of the WebSocket servers in the chess game architecture is to handle user authentication and authorization.

<p>False (B)</p> Signup and view all the answers

Name three game termination states that the chess game system should be able to ensure.

<p>Checkmate, resignation, stalemate</p> Signup and view all the answers

To ensure the chess game system can handle a large number of concurrent games, the ______ is used to distribute the load among various game engine instances.

<p>Game Engine Manager</p> Signup and view all the answers

Match each component of the comment moderation system with its primary function:

<p>User Authentication Service = Verifies the identity of users attempting to log in to the system. Comment Service = Handles the submission, storage, and retrieval of user comments. Comment Moderation Service = Automatically reviews and manages comments to ensure compliance with community guidelines. AI/ML Engine = Analyzes comments for toxic content, spam, or other violations using machine learning models.</p> Signup and view all the answers

Which of the following is NOT a functional requirement for the comment moderation system?

<p>High Availability (A)</p> Signup and view all the answers

The comment moderation system is designed to allow users to edit their comments after they have been published.

<p>False (B)</p> Signup and view all the answers

In the comment moderation system, what is the role of the Pub-Sub mechanism?

<p>To forward user comments to the comments moderation service</p> Signup and view all the answers

The ______ is responsible for distributing the load evenly across servers in the comment moderation system.

<p>Load Balancer</p> Signup and view all the answers

Match the following comment moderation requirements to their description:

<p>Availability = The system should be consistently accessible and operational to filter comments. Scalability = The system should be able to handle a large volume of comments without performance degradation. Reliability = The system should continue to function correctly even if some components fail. Consistency = All users should see the same state of a comment at any given time.</p> Signup and view all the answers

In the comment moderation system, what is the primary purpose of the AI/ML engine?

<p>To review and filter comments for inappropriate content. (A)</p> Signup and view all the answers

The comment moderation system prioritizes immediate display of all comments, with moderation occurring only after the comment has been publicly visible.

<p>False (B)</p> Signup and view all the answers

What type of notification should the comment moderation system send to users?

<p>Notifications about actions taken on their comments</p> Signup and view all the answers

In the comments moderation system, the component responsible for verifying users' identities at a large scale is the ______.

<p>User Authentication Service</p> Signup and view all the answers

Match each component involved in the high-level design of the comment moderation system with its role:

<p>User Authentication Service = Verifies user identities for system access. Comment Service = Handles submission, storage, and retrieval of comments. Comments Moderation Service = Automates the review and management of user comments. AI/ML Engine = Analyzes comments using algorithms to identify and filter inappropriate content.</p> Signup and view all the answers

Which data is MOST important for the recommendation engine to create and manage user profiles?

<p>User's demographics, interests, preferences, and past interactions (A)</p> Signup and view all the answers

The recommendation engine should NOT update recommendations dynamically as users interact with the platform.

<p>False (B)</p> Signup and view all the answers

Name a process the recommendation engine might use for background processing to ensure response times are efficient.

<p>Data preprocessing, model training, and recommendation generation.</p> Signup and view all the answers

The recommendation engine must prioritize security against unauthorized data access and breaches by implementing specific techniques such as data ______ and encryption.

<p>anonymization</p> Signup and view all the answers

Match the component with the descriptions used in the recommendation engine.

<p>Data Collector = Ingests data into the big data processing system. Big Data Processing Systems = Analyzes raw data and derives useful insights. Off-Grid AI System = Trains predictive models offline to enhance recommendation accuracy. Recommendation Service = Stores user data and preferences in databases.</p> Signup and view all the answers

What is handled by the recommendation service in designing the recommendation engine?

<p>Storing user data and preferences (B)</p> Signup and view all the answers

The offline AI system receives data directly from user screens.

<p>False (B)</p> Signup and view all the answers

In the context of the short video recommendation engine, what is the role of the data collector?

<p>Ingests data into the big data processing system</p> Signup and view all the answers

The processed data from the big data processing system is fed into the ______, which trains predictive models offline to enhance recommendation accuracy.

<p>off-grid AI system</p> Signup and view all the answers

Associate non-functional requirements of a recommendation engine with the appropriate implementation detail.

<p>Scalability = Handling growing items without performance loss Low Latency = Providing quick real-time recommendation Privacy = Anonymizing and encrypting users' information Security = Preventing unauthorized data access</p> Signup and view all the answers

Among the data management considerations of the recommendation engine, which technique addresses unauthorized data access and breaches?

<p>Security Implementation (B)</p> Signup and view all the answers

The recommendation engine's design does include handling user data securely and implementing data anonymization and encryption techniques.

<p>True (A)</p> Signup and view all the answers

Why is it critical that the video recommendations be made in real-time?

<p>Because the engine needs to stay up-to-date on trends to deliver the best results.</p> Signup and view all the answers

In processing the function of deriving useful insights for the recommendation engine, a ______ is utilized to handle the analysis of data to get useful insights.

<p>big data processing system</p> Signup and view all the answers

Categorize the operational technologies that the recommendation engine employs during design.

<p>Recommendation Service = Stores user data and preferences in databases. Data Collector = Gathers data into the big data processing system. Big Data Processing System = Performs the data analysis. Offline AI system = Enhances performance and accuracy of suggestions.</p> Signup and view all the answers

Which big data processing system element processes information to enhance user suggestions’ performance and accuracy?

<p>Offline AI system (D)</p> Signup and view all the answers

The video of the recommendation engines’ load balancer directly hosts users video info .

<p>False (B)</p> Signup and view all the answers

What security measure protects against unauthorized access in video recommendation engine?

<p>Protecting Data or Encryption.</p> Signup and view all the answers

The method of processing the video for the recommendation engine for data analysis is ______.

<p>big data processing systems</p> Signup and view all the answers

Match the processes for ingesting data with the appropriate video for the recommendation results.

<p>Data Collector = Collects data for the processing into the big data process. Offline AI System = The processes and analyses can be implemented faster. Recommendation Service = stores users data into the video database. Big Data Processing Systems = They analyse and process data with the processed data that are fed to the system.</p> Signup and view all the answers

In the chess game system, which component is responsible for ensuring each move is valid according to chess rules?

<p>Game Engine (C)</p> Signup and view all the answers

In the comments moderation system, the user authentication service is solely responsible for filtering out offensive comments.

<p>False (B)</p> Signup and view all the answers

What is the primary role of the 'off-grid AI system' within the recommendation engine's architecture, and why is it designed to operate offline?

<p>The off-grid AI system is used to train predictive models offline. Running it offline allows for complex computations without impacting the latency of real-time recommendations.</p> Signup and view all the answers

In the chess game architecture, maintaining a latency of less than 100ms is a ______ requirement aimed at ensuring a responsive user experience.

<p>nonfunctional</p> Signup and view all the answers

Match the following components of the comments moderation system with their primary functions:

<p>User Authentication Service = Verifies user identity. Comment Service = Handles submission of the users comments. Comments Moderation Service = Reviews and manages user comments. AI/ML Engine = Filters comments based on content.</p> Signup and view all the answers

Flashcards

Create a game

Create a game for two players, white starts first, ranking/rating algorithms match players.

Record player status

Stores game information, player moves, and statistics (wins, losses, openings).

Valid moves

Enforces valid chess moves only, preventing undoing or canceling moves.

Display each move

Shows each move to both players in real-time.

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Game termination

Handles game termination states (checkmate, resignation, forfeit, stalemate).

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Latency

Latency should be within 100ms for smooth gameplay.

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Reliability

The system must continue functioning despite failures.

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Scalability

Supports at least 100 million monthly active users (MAU).

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Consistency

Data accessed by players must be accurate and up-to-date.

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Application Servers

Logs in players and manages matches using the game engine.

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Game Engine

Validates moves, manages game state, and enforces rules.

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Game Engine Manager

Manages game engine instances and distributes load.

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Websocket Servers

Provides real-time communication and move broadcasting.

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Persistent Layer

Stores all game states persistently.

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User Login

Authenticates users at scale.

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Comments Submission

Allows users to submit comments on published posts.

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Automated Comment Moderation

Automatically reviews and manages user comments.

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User Notification

Informs users about actions taken on their comments.

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User Reporting

Allows users to report comments.

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Availability

Must be highly available for filtering user comments.

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Scalability

Handles a large number of comments.

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Reliability

Must work properly even with component failures.

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Consistency

All users should see the same state of a comment at any time.

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Load Balancers

Distributes load evenly across servers.

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Pub-Sub

Forwards user comments to the moderation service.

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AI/ML Engine

Reviews and filters comments.

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Persistent Layer

Stores user data, comments, and metadata.

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User profiles

The system should be able to create and manage user profiles.

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Search and browse

Users should be able to search for specific videos or browse recommendations.

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Personalization

The system should customize and adjust recommendations for individual users based on their feedback.

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Real-time updates

The system should update recommendations dynamically as users interact.

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Offline processing

The system might require background processes for data preprocessing, model training, and recommendation generation.

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Scalability

The system should handle a growing number of users, items, and recommendations without compromising performance.

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Low latency

The system should be performant enough to provide real-time recommendations.

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Privacy

The system should handle users’ data securely and implement data anonymization and encryption techniques.

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Security

The system should implement techniques to prevent data from being unauthorizedly accessed and breached.

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Recommendation service

Stores users’ data and preferences.

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Data collector

Ingests data into the big data processing system.

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Big data processing system

Analyzes data and derives useful insights.

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Off-grid AI system

Predictive models improve recommendation accuracy.

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Study Notes

Chess Game System Design

  • The system is for a two-player online chess game.
  • It must be fast, reliable, and support 100 million monthly active users (MAU) playing one game a week.

Functional Requirements

  • Create a game for two online players, with white starting first. Ranking and rating algorithms select and direct players to a board.
  • Store game information, player moves, and statistics (wins, losses, best/worst openings).
  • Validate each move via an accurate chess program, with no move undo/cancel.
  • Display each move to both players in real time.
  • Ensure proper game termination states like checkmate, resignation, forfeit, or stalemate.

Nonfunctional Requirements

  • Latency should be within 100 ms.
  • The system should maintain correct functionality despite failures.
  • Support at least 100 million MAU.
  • Data accuracy is required for all players, reflecting the latest game state.

High-Level Design

  • Includes API gateways, load balancers, and different services.
  • Players log in via application servers and start matches using the game engine.
  • The game engine validates moves, manages game state, and enforces rules.
  • The game engine manager manages game engine instances and distributes load.
  • WebSocket servers facilitate real-time communication and move broadcasting.
  • Game states are logged into the persistent layer.

Comments Moderation System Design

  • An automated system to review and manage user comments before they appear on published content.
  • Similar to designing a live commenting system.

Functional Requirements

  • User authentication service to authenticate users.
  • Allow users to submit comments on posts.
  • Automatically review and manage user comments.
  • Notify users about the actions taken on their comments (published or rejected for violations).
  • Allow users to report comments for reanalysis.

Nonfunctional Requirements

  • High availability to filter comments.
  • Scalability to handle many comments.
  • Reliability despite component failures.
  • Consistency, so all users see the same comment state.

High-Level Design

  • Includes user authentication service, comment service, comment moderation service, and AI/ML engine.
  • Load balancers distribute load on servers.
  • The comment service uses pub-sub to forward comments to the moderation service.
  • The AI/ML engine reviews and filters comments.
  • A persistent layer stores user data, comments, and metadata.

Recommendation Engine Design

  • Designed to provide short video recommendations to millions of users.

Functional Requirements

  • Create and manage user profiles, capturing demographics, interests, preferences, ratings, reviews, and past interactions.
  • Enable users to search for specific videos or browse recommendations using categories/filters.
  • Customize recommendations based on user feedback.
  • Update recommendations dynamically as users interact with the platform.
  • Use background processes for data preprocessing, model training, and recommendation generation.

Nonfunctional Requirements

  • Handle a growing number of users, items, and recommendations.
  • Low latency for providing real-time recommendations.
  • Securely handle user data with anonymization and encryption techniques.
  • Implement techniques to prevent unauthorized data access and breaches.

High-Level Design

  • Comprises a load balancer, application servers, a recommendation service, a data collector, big data processing systems, databases, and an off-grid AI system.
  • The recommendation service stores user data and preferences, and reflects AI recommendations to users.
  • The data collector ingests data into the big data processing system for analysis and insight derivation.
  • Processed data is fed to the off-grid AI system for training predictive models to enhance user recommendations.

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