Design a Load Balancing for Google
Last updated: October 29, 2025
Quick Overview
Design a distributed load balancing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
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Design a distributed load balancing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during Technical Screen at Google. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. Google values engineers who can think about scalability from day one.
What the Interviewer Expects
- Clearly define functional and non-functional requirements
- Propose a reasonable high-level architecture with core components
- Choose appropriate data storage solutions with basic justification
- Discuss basic scaling strategies (horizontal scaling, caching)
- Identify potential bottlenecks and suggest simple solutions
Key Topics to Cover
How to Approach This
- Start by clarifying functional and non-functional requirements with the interviewer.
- Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
- Draw a high-level architecture first, then deep dive into 1-2 critical components.
- Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
- Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
- How would you migrate from a monolithic to a microservices architecture?
- What would the deployment pipeline look like for this system?
- How would you optimize costs as the system scales?
- How would you implement rate limiting to protect the system?
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Requirements
Functional Requirements
- Request Distribution: The load balancer should distribute incoming traffic across multiple servers to ensure no single server is overwhelmed.
- Health Checks: R...
Capacity Estimation
Assuming Google handles approximately 10 billion requests per day, we can perform a back-of-envelope calculation:
- Requests per second: 10 billion / (24 * 60 * 60) = ~115,740 requests per second....
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