Design a Analytics Service
Last updated: November 28, 2025
Quick Overview
Design a multi-tenant analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Palantir
November 28, 2025134
8
4,965 solved
Design a multi-tenant analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Palantir 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
- 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 handle a 10x increase in traffic overnight?
- How would you implement rate limiting to protect the system?
- How do you ensure data consistency across multiple services?
- How would you handle schema migrations with zero downtime?
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Requirements
Functional Requirements
- Multi-tenancy: The system should support multiple tenants (clients) with data isolation.
- Analytics Dashboard: Provide visualizations and reports based on user...
Capacity Estimation
Assuming we have 1 million users, each generating an average of 100 requests per day:
- Total Requests per Day: 1,000,000 users * 100 requests = 100,000,000 requests/day.
- Requests per Second...
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