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

Senior
May 2026

Summary

Google SWE system design round, one question the whole time: design a load balancer. Pretty sparse on details but that's kind of how these go.

Questions Asked (1)

Q1

Design a load balancer from scratch.

System DesignTechnical Trade-offs
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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then outline a high-level design covering load balancing algorithms, health checks, and scalability. Dive into trade-offs for key components like layer 4 vs layer 7, and discuss how to handle failures and dynamic scaling.

Pro tip: Emphasize that a load balancer is a distributed system itself, so you must consider its own high availability and failure modes. Mention that Google's Maglev is a real-world example of a scalable load balancer.

1. Clarify Requirements

Ask about expected traffic volume, latency requirements, protocol (TCP/UDP/HTTP), and whether it's for internal or external use. This shapes the design.

2. High-Level Design

Sketch the architecture: clients, load balancer, backend servers. Decide on layer 4 vs layer 7, and whether to use a centralized or distributed approach.

3. Load Balancing Algorithms

Discuss algorithms like round robin, least connections, consistent hashing, and their trade-offs. Explain how to handle session persistence if needed.

4. Health Checks and Failover

Describe how to detect unhealthy backends (active/passive checks) and remove them from rotation. Discuss how the load balancer itself achieves high availability.

5. Scalability and Performance

Address how to scale the load balancer (horizontal scaling, anycast, DSR) and optimize performance (connection pooling, caching, hardware acceleration).

Key Points to Mention

  • Layer 4 vs Layer 7 load balancing and their trade-offs
  • Load balancing algorithms: round robin, least connections, consistent hashing
  • Health checks and automatic failover
  • High availability of the load balancer itself (active-passive, active-active)
  • Scalability techniques: anycast, ECMP, distributed load balancing (e.g., Maglev)
  • Session persistence and sticky sessions

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