← Microsoft Interview Insights

Microsoft·Product Manager·Onsite - System Design / Architecture·Intermediate

Intermediate
May 2026

Summary

Microsoft PM interview with a single system design question. Pretty open-ended, not much else to go on.

Questions Asked (1)

Q1

Design a parking lot system.

System DesignProduct Sense & IdeationTechnical Trade-offs
Author's notes

Classic question but it opens up fast once you start talking through it.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the scope and requirements of the parking lot system, such as size, location, and user types. Then, outline a high-level design covering key components like entry/exit, payment, and space allocation, and dive into trade-offs and edge cases. Finally, discuss how you would measure success and iterate based on user feedback.

Pro tip: Anchor your design in a clear user journey and business goal (e.g., maximizing occupancy or reducing wait times), and explicitly tie technical choices back to those outcomes to show product sense.

1. Clarify Requirements

Ask questions to understand the scope: Is this for a single lot or a network? What types of vehicles? What are the peak hours? What are the key user personas (drivers, attendants, owners)?

2. Define Core Entities and Flows

Identify main components: parking spots, vehicles, entry/exit gates, payment systems, and user interfaces. Map out the end-to-end user flow from arrival to departure.

3. Design System Architecture

Propose a high-level architecture: how spots are allocated (e.g., first-come-first-served, reservation), how payments are processed, and how data is stored and synced across gates.

4. Address Trade-offs and Edge Cases

Discuss trade-offs like cost vs. scalability, real-time vs. batch updates, and handle edge cases such as lost tickets, payment failures, and full capacity.

5. Define Success Metrics and Iteration

Propose metrics like average wait time, occupancy rate, and revenue per spot. Suggest how to iterate based on data and user feedback.

Key Points to Mention

  • User personas and their pain points (e.g., drivers want fast entry/exit, owners want max revenue).
  • Scalability considerations: handling multiple lots, peak loads, and future expansion.
  • Technology choices: IoT sensors for spot detection, mobile app for reservations, license plate recognition.
  • Payment integration and security (PCI compliance, multiple payment methods).
  • Data analytics for dynamic pricing and occupancy prediction.
  • Failure modes and redundancy (e.g., offline mode, backup power).

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.