Design a large-scale Search Platform

Last updated: November 3, 2025

Quick Overview

Design a geo-distributed search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Doordash
System Design
Machine Learning Engineer
Doordash
November 3, 2025
Machine Learning Engineer
Onsite
System Design
Hard

1

4

3,840 solved


Design a geo-distributed search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Doordash asks this during the Onsite 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
  • 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
Load balancing and horizontal scaling
Security and authentication
Requirements gathering and capacity estimation
Partitioning and sharding strategies
Failure handling and fault tolerance
Consistency models and replication
How to Approach This
  1. Start by clarifying functional and non-functional requirements with the interviewer.
  2. Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
  3. Draw a high-level architecture first, then deep dive into 1-2 critical components.
  4. Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
  5. Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
  • How would you handle schema migrations with zero downtime?
  • What monitoring and alerting would you set up on day one?
  • How would you optimize costs as the system scales?
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Sample Answer
Requirements Clarification

Before diving into the architecture, clarify the scope with the interviewer. For large-scale Search Platform, key functional requirements include: wha...

Capacity Estimation

Estimate the scale to drive design decisions. Assume 100M DAU with an average of 10 actions per user per day = 1B requests/day ~ 12K QPS average, ~36K...


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