Build a distributed Load Balancing Pipeline
Last updated: April 14, 2026
Quick Overview
Design a distributed load balancing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Salesforce
April 14, 2026170
7
2,497 solved
Design a distributed load balancing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Salesforce typically last 45-60 minutes. You are expected to drive the conversation, starting from requirements gathering through to a detailed architecture. The interviewer will evaluate your ability to handle ambiguity and make practical engineering decisions.
What the Interviewer Expects
- Drive the design discussion proactively with minimal interviewer guidance
- Perform detailed capacity estimation and use it to inform design decisions
- Design for global scale with multi-region deployment and data consistency
- Deep dive into 2-3 critical components with implementation-level detail
- Address complex trade-offs: CAP theorem, eventual consistency, conflict resolution
- Discuss operational excellence: deployment strategy, chaos engineering, SLOs/SLIs
- Propose a phased rollout plan from MVP to full-scale system
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 handle schema migrations with zero downtime?
- How would you migrate from a monolithic to a microservices architecture?
- What monitoring and alerting would you set up on day one?
- What would the deployment pipeline look like for this system?
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Requirements
- Functional Requirements:
- Support for millions of requests per second, ensuring efficient load balancing across multiple services.
- Implement rate limiting to protect backend services from...
Capacity Estimation
Assuming Salesforce handles around 1 billion requests per day:
- Requests per second (RPS):
- 1 billion requests/day = 1 billion / (246060) ≈ 11,574 RPS.
- Concurrent connections: Assumin...
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