System Design Interview: How Social Media News Feeds Work | Fan-Out, Caching & Scalability

Описание: Are you learning social media feed design or preparing for your next system design interview? This video gives you an in-depth, interview-focused breakdown of everything you need to know to design scalable and efficient social media feeds—like Facebook News Feed, Twitter Timeline, or Instagram Home.

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📚 What’s Covered in This Video?

1. Problem Overview:

Understand the functional requirements for a social media feed:

Users can post content (text, images, videos)

Users can follow others

Feeds must be fast, highly available, and eventually consistent

2. Read vs. Write Optimization:

The social media feed system is highly read-heavy—one post can be read by thousands or millions.

Why we optimize the write path for faster feed reads.

3. Fan-Out Mechanisms Explained:

Fan-out on Read (Pull Model):

Feeds built when requested. Suits small follower sets, but slow for large-scale.

Fan-out on Write (Push Model):

Feeds precomputed and updated when a post is created—making read queries lightning fast.

4. High-Level Architecture:

Writing a post:

Request handled by Post Service → Post DB (Cassandra recommended) → Kafka message queue

Fan-out Service:

Consumes events, gets followers, injects post ID into each follower’s feed list (Redis cache for speed)

Reading a feed:

Fast query from Redis returns a list of post IDs, hydrated later for content

5. Handling Celebrities & Scale:

Hybrid Approach:

For normal users: Fan-out-on-write

For celebrity accounts (millions of followers): Fan-out-on-read, merge celebrity posts at read time for scalability and performance

Prevent system overload when celebrities post!

6. Important Architectural Components:

Message Queues (Kafka): Decoupling for async, reliable feed updates

In-Memory Cache (Redis):

Redis LPUSH, LTRIM, and LRANGE for managing user feed lists efficiently

Follower Graph Database (Redis/NoSQL): Mapping who follows whom at massive scale

7. Edge Cases, Challenges & Best Practices:

Feed consistency vs. latency: Eventual consistency is acceptable for most cases

Caching strategies for hot feeds

Handling billions of posts and hundreds of millions of active users

🔑 Key Interview Takeaways:

Always classify feeds as read-heavy systems; justify fan-out-on-write

Know the trade-offs between fan-out-on-read, fan-out-on-write, and hybrid solutions

Use message queues and Redis list operations in your design to show real-world understanding

Demonstrate handling of celebrity problem with a scalable hybrid approach

Who Should Watch?

Software engineers prepping for system design & backend engineering interviews

Students learning distributed systems, backend architecture, or caching strategies

Developers building their own social networking apps or feeds

Boost your interview success—learn core architecture patterns, handle scaling like a pro, and impress with cache + queue knowledge.

Effective Hashtags:
#SystemDesign #SocialMediaFeed #TechInterview #NewsFeed #BackendEngineering #Scalability #FanOut #RedisCache #Kafka #Microservices #FeedArchitecture #EngineeringInterview #DistributedSystems #Programming

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