Design a Caching for Palo Alto Networks
Last updated: October 17, 2025
Quick Overview
Design a geo-distributed caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Palo Alto Networks
October 17, 20252
6
2,495 solved
Design a geo-distributed caching 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 a 10x increase in traffic overnight?
- How would you handle schema migrations with zero downtime?
- What would the deployment pipeline look like for this system?
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Requirements
Functional Requirements
- Geo-distributed Caching: Cache data geographically close to users to minimize latency.
- Request Handling: Support millions of read requests per second (QPS) wi...
Capacity Estimation
Assuming Palo Alto Networks serves 100 million users globally:
- Requests per Second (QPS): If each user generates 1 request every 10 seconds, total QPS = 100M / 10 = 10 million requests/second. -...
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