Build a scalable Recommendation Pipeline

Last updated: April 4, 2026

Quick Overview

Design a scalable recommendation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Doordash
System Design
Software Engineer
Doordash
April 4, 2026
Software Engineer
System Design Round
System Design
Medium

173

12

1,362 solved


Design a scalable recommendation system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

System design interviews at Doordash typically last 45-60 minutes. You are expected to drive the conversation, starting from requirements gathering through to a detailed architecture. The interviewer will evaluate your ability to handle ambiguity and make practical engineering decisions.

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
Failure handling and fault tolerance
Message queues and async processing
High-level architecture and component design
Monitoring, logging, and alerting
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 a region-wide outage?
  • How do you ensure data consistency across multiple services?
  • How would you handle a 10x increase in traffic overnight?
  • How would you handle schema migrations with zero downtime?
Practice a Similar Problem on Codemia

Solve a related problem with our interactive workspace, get AI feedback, and view detailed solutions.

Solve on Codemia
Sample Answer
Requirements

Functional Requirements

  1. User Personalization: The system should provide personalized restaurant and food recommendations based on user preferences, past orders, and ratings.
  2. **Real-time ...
Capacity Estimation

Back-of-Envelope Calculations

  • Daily Active Users (DAUs): Assume 10 million users.
  • Requests per User: Assume an average of 5 recommendation requests per user per day.
  • **Total Recommen...

Submit Your Answer
Markdown supported

Related Questions