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:
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The system should
collect news articles
from many different news providers (e.g., CNN, BBC, local newspapers) using:
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Web crawlers (for sites without APIs).
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RSS feeds or publisher APIs when available.
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The system should
normalize and store
collected articles with consistent metadata:
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Title, body, URL, publish time, source, author.
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Category (e.g., politics, sports, tech) and language.
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The system should support
logged-in users
who have:
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Subscriptions to specific publishers/sources.
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Category/topic preferences (e.g., more sports, less politics).
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For each logged-in user, the system should display a
personalized news feed
, taking into account:
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User’s subscriptions.
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User’s category/topic preferences.
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Freshness and popularity of articles.
Non-functional requirements and constraints (you may make reasonable assumptions, but be explicit):
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Large scale: potentially tens of millions of daily active users.
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High read throughput: most requests are for reading the news feed.
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Reasonable freshness: new articles should appear in user feeds within a few minutes of being published.
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High availability and low latency for feed retrieval (e.g., p95 < 200–300 ms).
In your design, cover at least the following aspects:
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Requirements and APIs
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Clarify functional and non-functional requirements.
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Define main APIs or endpoints for clients (web/mobile) to fetch the news feed and manage preferences.
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High-level Architecture
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Major components and services (e.g., crawler, content ingestion pipeline, storage, feed/personalization service).
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How data flows from publishers to the end-user feed.
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Data Storage and Indexing
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How you will store articles, metadata, and user preferences.
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How to support efficient querying (by category, recency, popularity, user interests).
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Crawling & Ingestion Pipeline
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How crawlers/RSS/API consumers are scheduled and scaled.
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How content is parsed, deduplicated, categorized, and filtered.
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Personalization & Ranking
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How to build a personalized feed based on user subscriptions and category preferences.
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Basic ranking logic (you can assume heuristic or ML-based ranking, but describe the approach conceptually).
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Scalability, Caching, and Availability
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Strategies to handle high read traffic and keep latency low.
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Use of caching, CDNs, sharding, and replication.
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Freshness, Consistency, and Trade-offs
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How to balance freshness of news with system load and cache efficiency.
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Any relevant consistency or CAP-theorem trade-offs you would make.
Explain your design step-by-step and justify key trade-offs.