Design a multi-tenant Content Delivery System
Last updated: June 14, 2026
Quick Overview
Design a multi-tenant content delivery system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Splunk
System Design
Software Engineer
Splunk
June 14, 2026Software Engineer
System Design Round
System Design
Hard
60
14
4,409 solved
Design a multi-tenant content delivery system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Splunk 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
- Drive the design discussion proactively with minimal interviewer guidance
- Perform detailed capacity estimation and use it to inform design decisions
- Design for global scale with multi-region deployment and data consistency
- Deep dive into 2-3 critical components with implementation-level detail
- Address complex trade-offs: CAP theorem, eventual consistency, conflict resolution
- Discuss operational excellence: deployment strategy, chaos engineering, SLOs/SLIs
- Propose a phased rollout plan from MVP to full-scale system
Key Topics to Cover
Message queues and async processing
Monitoring, logging, and alerting
Caching strategies (local, distributed, CDN)
API design and rate limiting
Security and authentication
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
- What happens if one of your database nodes goes down?
- How would you optimize costs as the system scales?
- How would you migrate from a monolithic to a microservices architecture?
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