templates
Newsfeed
Overview
Requirements
Functional Requirements
- Post multimedia content (text, image)
- Browse the feed
- Interact with content (like, comment)
- Follow and unfollow users
- Search for users and hashtags
Non-Functional Requirements
- Low Latency
- High Availability
- Consistency
- Scalability
- Security and Privacy
System Architecture
Key Strategies
- Fan-Out/Fan-In Strategy
- Read-Your-Writes Consistency
- Data replication across servers
Architectural Styles
- Event-Driven Architecture
- Microservices Structure
Design Patterns
Fan-Out/Fan-In Strategy
- Push Model: Updates are directly pushed to all followers' feeds.
- Pull Model: Followers fetch updates from the original poster's feed.
- Hybrid Model: Combines push for critical updates and pull for less urgent ones.
Event Sourcing Pattern
- Store Events
- Replay Events
Sharding Pattern
- Shard by user region
- Shard by activity level
System Architecture
1. Authentication Flow
- Client initiates secure authentication by requesting a token from Token Server. After validating credentials, Token Server issues a secure JWT token.
- Using the authenticated token, Client uploads media to Media Storage. The system then processes uploads, generates optimized thumbnails, and prepares content for CDN distribution.
2. Post Creation Process
- Client assembles post content (text/media) and transmits through API Gateway, which manages rate limiting and performs preliminary request validation.
- Web Server conducts thorough content validation and permission checks. Queue system handles traffic management and ensures reliable message delivery.
3. Content Distribution Strategy
- Work Server queries User Relationship DB to determine follower relationships and distribution method.
- Fanout Strategy (< 10K followers): Immediately pushes new content to followers' Timeline Cache, enabling real-time updates.
- Pull Strategy (> 10K followers): Implements lazy loading where content is retrieved when followers access their feed, optimizing system resources.
Database Design
API Design
class NewsFeedAPI:def create_post(user_id: UUID, content: string, media_files: List[File]) -> Post:"""Create a new post with optional media attachments"""# 1. Validate user and contentvalidate_user(user_id)validate_content(content)# 2. Upload media files to CDN/Storagemedia_urls = media_service.upload_files(media_files)# 3. Create post in databasepost = Post(user_id=user_id,content=content,media_urls=media_urls)db.posts.insert(post)# 4. Publish event to message queue for async processingevent = {"type": "NEW_POST","post_id": post.id,"user_id": user_id}message_queue.publish("post_events", event)return postdef get_newsfeed(user_id: UUID, page: int, limit: int) -> List[Post]:"""Get user's newsfeed with pagination"""# 1. Try to get from cache firstcached_feed = cache.get(f"feed:{user_id}:{page}")if cached_feed:return cached_feed# 2. Get timeline entries from cache/databasetimeline_entries = timeline_cache.get_entries(user_id=user_id,offset=page * limit,limit=limit)# 3. Fetch full post datapost_ids = [entry.post_id for entry in timeline_entries]posts = db.posts.find({"id": {"$in": post_ids}})# 4. Apply ranking algorithmranked_posts = ranking_service.rank_posts(posts, user_id)# 5. Cache the resultscache.set(f"feed:{user_id}:{page}",ranked_posts,expire=300 # 5 minutes)return ranked_posts
Interview Questions
How would you ensure low latency for instant updates across a globally distributed user base?
- Implement multi-region CDNs with edge caching for static content and frequently accessed posts
- Use multi-level caching strategy (browser, CDN, application, database) with Redis/Memcached
- Shard databases by user_id with read replicas for heavy read operations
How would you guarantee consistency in the news feed across multiple devices?
- Implement version vectors or logical clocks to track update sequence across devices
- Use optimistic concurrency control with last-write-wins for conflict resolution
- Maintain a central source of truth with event sourcing for state reconstruction
How would you design a system to identify and display trending hashtags in real-time?
- Use Apache Kafka/Kinesis for real-time stream processing of hashtag usage
- Implement sliding window counters with Redis for temporal trending analysis
- Apply decay factors to older data for recency-biased trending algorithms
How would you track and display real-time analytics for trending content?
- Use stream processing (Apache Flink/Storm) for real-time event aggregation
- Implement counter sharding with eventual consistency for high-volume metrics
- Maintain pre-aggregated statistics in Redis with periodic persistence to database
How would you design a system to deliver real-time notifications to millions of users?
- Use WebSocket connections with connection pooling for persistent connections
- Implement message queues (RabbitMQ/Kafka) for reliable message delivery
- Deploy notification service across multiple regions with local presence
How would you handle data hotspots from viral content?
- Implement adaptive caching with automatic promotion of viral content
- Use rate limiting and request throttling based on user/content popularity
- Deploy dynamic read replicas for hot data partitions
How would you ensure data privacy and compliance with regulations?
- Implement end-to-end encryption for sensitive data with proper key management
- Use role-based access control with detailed audit logging of all data access
- Deploy data retention policies with automated deletion/anonymization workflows