Architect a real-time Logging Engine
Last updated: February 6, 2026
Quick Overview
Design a real-time logging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Doordash
February 6, 202620
12
4,958 solved
Design a real-time logging system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Doordash asks this during the Technical Screen 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
- Clearly define functional and non-functional requirements
- Propose a reasonable high-level architecture with core components
- Choose appropriate data storage solutions with basic justification
- Discuss basic scaling strategies (horizontal scaling, caching)
- Identify potential bottlenecks and suggest simple solutions
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?
- What would the deployment pipeline look like for this system?
- How would you implement rate limiting to protect the system?
- What happens if one of your database nodes goes down?
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Requirements
Functional Requirements
- Real-time Logging: Capture logs from various microservices in real-time.
- Search and Filter: Allow users to search and filter logs based on parameters like tim...
Capacity Estimation
Assuming DoorDash processes around 10 million requests per day, we can estimate the logging load:
- Requests per second: 10,000,000 requests / 86400 seconds = ~115.74 requests/sec.
- Log Size:...
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