System Design - Design a News Aggregator

A news aggregator system design question for a Netflix interview typically centers on massive scale, real-time updates, and deep personalization. Netflix interviewers value intellectual honesty and your ability to navigate high-latency budgets and global distribution.

Problem Statement: Designing a Global News Aggregator

The Challenge:"Design a real-time news aggregator similar to Google News that fetches articles from thousands of global sources (RSS, APIs, webhooks) and serves a personalized, low-latency feed to 200 million daily active users (DAU)."

1. Functional Requirements

• Ingestion: Support thousands of sources with varying update frequencies.
• Deduplication: Identify and group "near-duplicate" stories (multiple outlets reporting the same event) to keep the feed clean.
• Personalization: Rank stories based on user interests, history, and geographical relevance.
• Search: Allow users to search for news by keywords or topics.

2. Non-Functional Requirements

• Freshness: New articles must appear in the feed within minutes of publication.
• Low Latency: The personalized feed should load in under 200ms globally.
• High Availability: The system must handle massive traffic spikes during "breaking news" events.

3. Netflix-Specific "Deep Dives"

In a Netflix-style interview, you should expect to discuss these advanced topics:

• Global Distribution: How do you serve news to users in different regions while maintaining consistent personalization?
• Operational Resilience: What happens if the ingestion pipeline fails during a global event? How does your system degrade gracefully?
• Fan-out Strategy: For "breaking news," how do you push updates to millions of active sessions simultaneously without overwhelming your database?

4. Recommended High-Level Architecture Components

Component | Responsibility --- | --- Crawler/Ingestor | Fetches and normalizes data from RSS/APIs. Deduplication Engine | Uses MinHash or SimHash to cluster similar stories. Personalization Service | Generates a custom feed based on user telemetry. Edge Cache (CDN) | Stores static assets and regional feeds to reduce latency.

Would you like me to expand on the data modeling for the article storage or the ranking algorithm for the personalized feed?

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