Build a distributed Load Balancing Pipeline
Last updated: April 7, 2026
Quick Overview
Design a distributed load balancing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Databricks
April 7, 202661
9
944 solved
Design a distributed load balancing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Databricks 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
- Systematically gather requirements and estimate capacity (QPS, storage, bandwidth)
- Design a scalable architecture with clear component responsibilities
- Make well-reasoned database and caching decisions with trade-off analysis
- Address consistency vs availability trade-offs specific to the use case
- Discuss partitioning strategy, replication, and data modeling
- Cover failure handling, monitoring, and alerting strategies
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 optimize costs as the system scales?
- What would the deployment pipeline look like for this system?
- How would you migrate from a monolithic to a microservices architecture?
- How do you ensure data consistency across multiple services?
Practice a Similar Problem on Codemia
Solve a related problem with our interactive workspace, get AI feedback, and view detailed solutions.
Solve on CodemiaSample Answer
Requirements
Functional Requirements
- Request Handling: The system must accept millions of incoming requests per second (QPS) and distribute them to multiple backend services.
- **Load Balancing Algorit...
Capacity Estimation
To handle millions of requests, we estimate the following:
- Expected Traffic: Assume 10 million requests per second (QPS).
- Data Handling: Assuming each request is approximately 1 KB in size...
Submit Your Answer
