Architect a real-time Load Balancing Engine
Last updated: March 21, 2026
Quick Overview
Design a real-time load balancing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Atlassian
March 21, 202681
7
3,779 solved
Design a real-time load balancing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Atlassian asks this during the Onsite to assess your architectural thinking. They want to see how you decompose a complex problem, choose appropriate technologies, and reason about failure modes. Strong candidates proactively discuss monitoring, alerting, and operational concerns.
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
- What happens if one of your database nodes goes down?
- How would you migrate from a monolithic to a microservices architecture?
- How would you handle schema migrations with zero downtime?
- How would you handle a 10x increase in traffic overnight?
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Requirements
Functional Requirements
- Load Balancing: Distribute incoming requests evenly across multiple application servers to ensure optimal resource utilization.
- Real-Time Metrics: Monitor the...
Capacity Estimation
Assuming Atlassian expects to handle approximately 100 million requests per day, we can break this down:
- Requests per second: 100 million requests / 86400 seconds ≈ 1157 requests/second.
- **Pea...
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