Architect a real-time Analytics Engine
Last updated: May 18, 2026
Quick Overview
Design a real-time analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Cloudflare
May 18, 20267
6
3,868 solved
Design a real-time analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Cloudflare 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 do you ensure data consistency across multiple services?
- How would you handle a 10x increase in traffic overnight?
- How would you optimize costs as the system scales?
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Requirements
- Functional Requirements:
- Process and analyze millions of requests in real-time, providing analytics on traffic patterns, user behavior, and performance metrics.
- Support various data ...
Capacity Estimation
To estimate the capacity, we will consider the following factors:
- QPS: Assume we expect 10 million requests per second (QPS).
- Data Size: Each request generates approximately 1KB of ana...
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