Molocoads·Software Engineer·Onsite - System Design / Architecture·Intermediate

Intermediate

Jun 2026

Summary

Round 2 at Molocoads for a software engineering role, system design with a Korean interviewer who was pretty chill. Just the one question but it had some depth to it.

Questions Asked (1)

Design a real-time comment system similar to Facebook's.

System DesignAPI & IntegrationsTechnical Trade-offs

Author's notes

This is one of those questions where you think you know where to start and then realize halfway through that the 'real-time' part is doing a lot of heavy lifting.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale (e.g., number of concurrent users, latency targets, consistency needs). Then design a high-level architecture covering data flow from client to storage, focusing on real-time delivery mechanisms and trade-offs. Finally, dive into key components like WebSockets, pub/sub, and data modeling, discussing scalability and reliability.

Pro tip: Emphasize the trade-offs between different real-time technologies (e.g., WebSockets vs. long polling) and how you would handle failure scenarios like dropped connections or message loss. Showing awareness of operational concerns like monitoring and rate limiting can set you apart.

1. Clarify Requirements and Scale

Ask questions to understand functional and non-functional requirements: expected number of concurrent users, read/write ratio, latency, consistency, and features like threading, likes, and notifications.

2. High-Level Architecture

Outline the main components: clients, API gateway, comment service, real-time delivery service, storage, and cache. Describe the flow of posting a comment and receiving updates.

3. Real-Time Delivery Mechanism

Choose and justify a real-time communication method (e.g., WebSockets, SSE, long polling). Discuss how to scale it with pub/sub (e.g., Redis, Kafka) and handle connection management.

4. Data Modeling and Storage

Design the data schema for comments, including indexing for efficient retrieval. Choose appropriate databases (e.g., SQL for consistency, NoSQL for scale) and discuss caching strategies.

5. Scalability, Reliability, and Trade-offs

Address scaling (sharding, replication), fault tolerance (retries, idempotency), and trade-offs (consistency vs. availability, cost vs. performance). Mention monitoring and rate limiting.

Key Points to Mention

WebSockets for bidirectional real-time communication, with fallback to long polling for compatibility.
Pub/sub system (e.g., Redis Pub/Sub, Kafka) to decouple comment ingestion from delivery and enable fan-out to multiple subscribers.
Data partitioning and sharding strategies to handle high write throughput and large volumes.
Caching frequently accessed comments (e.g., Redis) to reduce database load and improve latency.
Handling offline users and missed comments via push notifications or sync on reconnect.
Trade-offs between consistency and availability (CAP theorem) and how to choose based on product requirements.

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