System Design: Personalized News Aggregation Service

Design a large-scale news aggregation system similar to Google News or other news aggregator products.

The key functional requirements are:

• The system should collect news articles from many different news providers (e.g., CNN, BBC, local newspapers) using:
  • Web crawlers (for sites without APIs).
  • RSS feeds or publisher APIs when available.
• The system should normalize and store collected articles with consistent metadata:
  • Title, body, URL, publish time, source, author.
  • Category (e.g., politics, sports, tech) and language.
• The system should support logged-in users who have:
  • Subscriptions to specific publishers/sources.
  • Category/topic preferences (e.g., more sports, less politics).
• For each logged-in user, the system should display a personalized news feed , taking into account:
  • User’s subscriptions.
  • User’s category/topic preferences.
  • Freshness and popularity of articles.

Non-functional requirements and constraints (you may make reasonable assumptions, but be explicit):

• Large scale: potentially tens of millions of daily active users.
• High read throughput: most requests are for reading the news feed.
• Reasonable freshness: new articles should appear in user feeds within a few minutes of being published.
• High availability and low latency for feed retrieval (e.g., p95 < 200–300 ms).

In your design, cover at least the following aspects:

1. Requirements and APIs
   • Clarify functional and non-functional requirements.
   • Define main APIs or endpoints for clients (web/mobile) to fetch the news feed and manage preferences.
2. High-level Architecture
   • Major components and services (e.g., crawler, content ingestion pipeline, storage, feed/personalization service).
   • How data flows from publishers to the end-user feed.
3. Data Storage and Indexing
   • How you will store articles, metadata, and user preferences.
   • How to support efficient querying (by category, recency, popularity, user interests).
4. Crawling & Ingestion Pipeline
   • How crawlers/RSS/API consumers are scheduled and scaled.
   • How content is parsed, deduplicated, categorized, and filtered.
5. Personalization & Ranking
   • How to build a personalized feed based on user subscriptions and category preferences.
   • Basic ranking logic (you can assume heuristic or ML-based ranking, but describe the approach conceptually).
6. Scalability, Caching, and Availability
   • Strategies to handle high read traffic and keep latency low.
   • Use of caching, CDNs, sharding, and replication.
7. Freshness, Consistency, and Trade-offs
   • How to balance freshness of news with system load and cache efficiency.
   • Any relevant consistency or CAP-theorem trade-offs you would make.

Explain your design step-by-step and justify key trade-offs.