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System Design Interview Prep: Your Last-Minute Survival Guide

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Overview of System Design Interviews

Multiple-Choice Questions for System Design Interview

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Design Overview

Key Components Explained

  1. User Interface (WebApp): The front-end platform where users engage with the service, including functionalities like photo and video uploads, liking, commenting, and browsing feeds and stories.
  2. API Gateway: Manages incoming requests and directs them to the appropriate backend services.
  3. Load Balancer: Distributes traffic among multiple backend service instances to maintain availability and scalability.
  4. Authentication Service: Oversees user logins, registrations, and credential validation.
  5. User Service: Manages user data and interactions, including profiles and follow/unfollow actions, while caching frequently accessed data.
  6. Media Service: Handles the upload, retrieval, and storage of media files, caching frequently accessed media.
  7. Comment Service: Manages post comments, enabling creation, retrieval, and deletion, while caching common comments.
  8. Notification Service: Sends real-time notifications regarding activities like new likes and comments, caching notifications for quick access.
  9. Feed Service: Generates and retrieves user feeds by aggregating posts from followed users and recommendations, caching results for fast access.
  10. Search Service: Offers search capabilities across the platform to find users, posts, and hashtags, utilizing an optimized search index.
  11. Story Service: Manages ephemeral user stories that disappear after 24 hours, caching frequently accessed stories.
  12. User Database (UserDB): Stores user-related data, such as profiles and connections.
  13. Media Database (MediaDB): Contains metadata for media files.
  14. Blob Storage: Dedicated to large media files like photos and videos.
  15. Comment Database (CommentDB): Retains comments on posts.
  16. Notification Database (NotificationDB): Holds notifications for users.
  17. Feed Database (FeedDB): Stores precomputed user feeds to enhance retrieval speeds.
  18. Search Index: Optimized index for rapid search queries across user data and posts.
  19. Story Database (StoryDB): Maintains story-related data.

Caching Layers

  • MediaCache: Stores frequently accessed media files.
  • CommentCache: Caches commonly accessed comments.
  • NotificationCache: Enables quick access to notifications.
  • FeedCache: Stores generated feeds for improved retrieval speed.
  • StoryCache: Caches frequently accessed stories.
  • (Optional) UserCache: Caches often accessed user data.

Managing Large Data Volumes

  • Sharding: Distributes data across multiple databases to enhance performance.
  • Replication: Copies data across servers for high availability and fault tolerance.
  • Partitioning: Divides large tables to optimize performance and manage data growth.

Efficient Media Storage and Retrieval

  • CDN Integration: Utilizes a Content Delivery Network (CDN) to cache and deliver media files, reducing latency.
  • Blob Storage: Stores media files in scalable solutions like AWS S3 or Google Cloud Storage.

Real-Time Notifications

  • Push Notifications: Employs WebSockets or push services for real-time updates.
  • Polling: Implements efficient polling for updates without overwhelming servers.

Efficient Feed Generation

  • Precomputation: Prepares user feeds in advance to minimize generation time.
  • Ranking Algorithms: Prioritizes posts based on relevance and user interactions.

Search Functionality

  • Full-Text Search: Leverages search engines to facilitate comprehensive search capabilities.
  • Indexing: Continuously updates the search index for quick queries.

User Roles and Permissions

  • Role-Based Access Control (RBAC): Defines roles with specific permissions to control feature access.
  • Permission Checks: Ensures users can only perform authorized actions.

Storage Optimizations

  • Caching: Implements caching systems to reduce database load and enhance response times.
  • Data Compression: Compresses data to lower storage costs.

Click HERE to return to the Table of Contents for more system design examples.

Questions

1. What is the primary function of Instagram?

  1. File Storage
  2. Social Networking
  3. Online Shopping
  4. Cloud Computing

> Answer: B > Explanation: Instagram primarily serves as a social networking platform for photo and video sharing.

2. Which database is most suitable for storing user profiles on Instagram?

  1. SQL
  2. NoSQL
  3. Flat File
  4. XML

> Answer: A > Explanation: SQL databases are best for structured data like user profiles.

3. What data model is best for Instagram's feed?

  1. Relational Model
  2. Graph Model
  3. Document Model
  4. Key-Value Model

> Answer: C > Explanation: A document model, often with NoSQL databases, is ideal for the diverse data in Instagram's feed.

4. Which technology is commonly used to cache frequently accessed data in Instagram?

  1. Redis
  2. MySQL
  3. MongoDB
  4. Hadoop

> Answer: A > Explanation: Redis is favored for caching due to its high performance.

5. How does Instagram ensure high availability of its services?

  1. Single Data Center
  2. Multiple Data Centers
  3. Backup Tapes
  4. Local Servers

> Answer: B > Explanation: Instagram utilizes multiple data centers for high availability.

6. Which component handles user authentication?

  1. Frontend Server
  2. Authentication Service
  3. Database
  4. Caching Layer

> Answer: B > Explanation: The Authentication Service manages user login and authentication.

7. What role does a CDN play for Instagram?

  1. Store User Data
  2. Deliver Content Quickly
  3. Handle Authentication
  4. Manage Databases

> Answer: B > Explanation: A CDN accelerates content delivery by caching it across distributed servers.

8. Which storage solution does Instagram use for media?

  1. Local Disk
  2. Amazon S3
  3. SQL Database
  4. Redis

> Answer: B > Explanation: Instagram commonly employs Amazon S3 for storing media files.

9. What method does Instagram use to manage high read request volumes?

  1. Load Balancer
  2. Write Optimized Database
  3. Single Server
  4. Batch Processing

> Answer: A > Explanation: Load balancers distribute requests to multiple servers, handling high read demands.

10. How does Instagram maintain data consistency across servers?

  1. Eventual Consistency
  2. Strong Consistency
  3. Local Consistency
  4. No Consistency

> Answer: A > Explanation: Eventual consistency allows updates to propagate to all nodes over time.

... [continue with additional questions in a similar format] ...

Conclusion

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