Design a large-scale Analytics Platform
Last updated: February 5, 2026
Quick Overview
Design a event-driven analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Palo Alto Networks
February 5, 2026111
11
2,608 solved
Design a event-driven analytics system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Palo Alto Networks 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 handle schema migrations with zero downtime?
- How do you ensure data consistency across multiple services?
- How would you implement rate limiting to protect the system?
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Requirements
Functional Requirements
- Event Ingestion: The system must handle millions of event requests per second from various security devices and applications.
- Real-time Analytics: Provide rea...
Capacity Estimation
To estimate capacity:
- Requests Per Second (QPS): Assume we expect 10 million events per day, which translates to approximately 115 QPS (10M events / (24 * 60 * 60)).
- Storage Needs: If each...
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