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rippling·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say
May 2026

Summary

Did a system design round at Rippling for a software engineer role, news feed design problem. The interviewer seemed pretty engaged throughout, which was a good sign.

Questions Asked (1)

Q1

Design a news feed system.

System DesignTechnical Trade-offsData Modeling
Author's notes

Felt pretty good about this one.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design a high-level architecture that separates feed generation (write path) from feed retrieval (read path). Focus on trade-offs between push and pull models, and discuss how to handle fan-out, ranking, and storage for scalability.

Pro tip: Emphasize the importance of defining SLAs and prioritizing freshness vs. completeness based on product needs; this shows you understand real-world constraints beyond just technical components.

1. Clarify Requirements

Ask about scale (users, posts per day), read/write ratio, latency requirements, and feed ranking criteria (chronological vs. algorithmic).

2. High-Level Design

Outline core components: post service, fan-out service, feed cache, and feed retrieval service. Decide on push vs. pull vs. hybrid model.

3. Deep Dive into Feed Generation

Explain how posts are fanned out to followers, including handling of celebrities (hybrid approach) and use of message queues for asynchronous processing.

4. Storage and Retrieval

Discuss data stores for posts (e.g., MySQL, Cassandra) and feeds (e.g., Redis, in-memory), and how to efficiently retrieve and rank feed items.

5. Scalability and Trade-offs

Address scaling reads/writes, caching strategies, consistency vs. availability, and trade-offs between push and pull models.

Key Points to Mention

  • Push vs. pull vs. hybrid fan-out models and their trade-offs
  • Handling high fan-out users (celebrities) with a hybrid approach
  • Use of caching (e.g., Redis) for fast feed retrieval
  • Ranking algorithm considerations (chronological vs. relevance-based)
  • Data partitioning and sharding strategies for scalability
  • Asynchronous processing with message queues for fan-out

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.