Design a real-time Search System
Last updated: January 1, 2026
Quick Overview
Design a real-time search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Grafana Labs
January 1, 202630
14
4,153 solved
Design a real-time search 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 Grafana Labs. 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. Grafana Labs values engineers who can think about scalability from day one.
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
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 migrate from a monolithic to a microservices architecture?
- How would you optimize costs as the system scales?
- What would the deployment pipeline look like for this system?
- How would you handle a 10x increase in traffic overnight?
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Requirements
Functional Requirements
- Real-time Search: Users can search through a vast dataset of logs and metrics in real-time with sub-second response times.
- Multi-region Support: The system must...
Capacity Estimation
Assumptions
- User Base: The system will support 10 million active users.
- Requests per User: Assuming an average of 5 searches per user per day.
- Peak Load: During peak hours, assum...
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