Design Recommendation Infrastructure for mobile apps

Last updated: October 6, 2025

Quick Overview

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

JPMorgan
System Design
Software Engineer
JPMorgan
October 6, 2025
Software Engineer
Technical Screen
System Design
Hard

34

4

4,052 solved


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

JPMorgan 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
  • 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
Partitioning and sharding strategies
Database selection and data modeling
High-level architecture and component design
Caching strategies (local, distributed, CDN)
Requirements gathering and capacity estimation
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?
  • What happens if one of your database nodes goes down?
  • What would the deployment pipeline look like for this system?
  • How would you migrate from a monolithic to a microservices architecture?
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 Profile Management: Ability to create and update user profiles including preferences, transaction history, and interactions.
  2. Recommendation Engine: Gener...
Capacity Estimation

Back-of-Envelope Calculations

  1. User Base: Assume 10 million active users.
  2. Requests: Each user generates an average of 5 recommendation requests per day, leading to 50 million requests...

Submit Your Answer
Markdown supported

Related Questions