Design Messaging Infrastructure for real-time analytics
Last updated: October 12, 2025
Quick Overview
Design a high-throughput messaging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Apple
October 12, 2025541
13
2,353 solved
Design a high-throughput messaging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during Onsite at Apple. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. Apple values engineers who can think about scalability from day one.
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
- What monitoring and alerting would you set up on day one?
- How would you handle a 10x increase in traffic overnight?
- What would the deployment pipeline look like for this system?
- How would you implement rate limiting to protect the system?
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Requirements
Functional Requirements
- High Throughput: Must handle millions of messages per second with low latency.
- Real-Time Analytics: Messages should be processed and analyzed in real time to ...
Capacity Estimation
Back-of-Envelope Calculations
- Estimated User Base: Assume 100 million active users.
- Message Rate: Each user sends an average of 10 messages per day. Total messages = 100M users * 10 ...
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