Architect a high-throughput Logging Engine
Last updated: October 3, 2025
Quick Overview
Design a high-throughput logging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Discord
System Design
Product Manager
Discord
October 3, 2025Product Manager
System Design Round
System Design
Medium
136
12
832 solved
Design a high-throughput logging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Discord asks this during the System Design Round to assess your architectural thinking. They want to see how you decompose a complex problem, choose appropriate technologies, and reason about failure modes. Strong candidates proactively discuss monitoring, alerting, and operational concerns.
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
Caching strategies (local, distributed, CDN)
Message queues and async processing
Database selection and data modeling
Security and authentication
Partitioning and sharding strategies
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 region-wide outage?
- How would you handle schema migrations with zero downtime?
- What would the deployment pipeline look like for this system?
- How do you ensure data consistency across multiple services?
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Requirements
Functional Requirements:
- High Throughput: The logging engine must handle millions of log requests per second (QPS) with minimal latency.
- Log Retention: Users should be able to specif...
Capacity Estimation
Back-of-Envelope Calculations:
- QPS Estimation: Assume Discord has approximately 150 million daily active users. If each user generates an average of 100 log events per day, this results in:...
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