Design a large-scale Analytics Platform
Last updated: February 14, 2026
Quick Overview
Design a event-driven analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
OpenAI
February 14, 202618
7
106 solved
Design a event-driven analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Software engineering fundamentals questions at OpenAI test your understanding of core CS concepts and their practical application. This Technical Screen question evaluates how you apply engineering principles to build maintainable, scalable software.
What the Interviewer Expects
- Explain the concept clearly with a practical example
- Discuss when and why to apply this principle
- Identify common mistakes and anti-patterns
- Compare with alternative approaches
Key Topics to Cover
How to Approach This
- Apply SOLID principles. Single Responsibility makes code testable, Open/Closed makes it extensible.
- Choose data structures based on access patterns, not familiarity.
- Prefer immutable data and message passing over shared mutable state for concurrency.
- Design APIs with RESTful conventions, versioning, meaningful errors, and pagination from day one.
Possible Follow-up Questions
- How would you measure the performance of this component in production?
- How would you handle backward compatibility?
- What testing strategy would you use for this component?
- What are the security implications of this design?
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Core Design Principles
For the analytics platform, the core design principles include Separation of Concerns, Scalability, and Event-Driven Architecture.
- Separation of Concerns: This principle applies b...
Architecture
The architecture of the analytics platform can be a Microservices architecture combined with Event Streaming using tools like Kafka.
- Ingestion Layer: This layer receives millions of ev...
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