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Design concurrency-safe shared payment account API

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's ability to design concurrency controls, idempotency handling, transactional guarantees, retry and failure semantics, and observability for a payments API to ensure correctness and durability under high concurrency and failures.

  • hard
  • Tesla
  • System Design
  • Software Engineer

Design concurrency-safe shared payment account API

Company: Tesla

Role: Software Engineer

Category: System Design

Difficulty: hard

Interview Round: Technical Screen

Scenario: Two users share one online payment account and submit payments at the same time. From an API and real-world engineering perspective, how would you ensure the balance remains correct and prevent double-spending? Specify request/response design, idempotency keys, concurrency control (e.g., optimistic or pessimistic locking, transactions), consistency guarantees, retries, and monitoring. Additionally, how would you scale the service to handle very high concurrency and massive request volumes?

Quick Answer: This question evaluates a candidate's ability to design concurrency controls, idempotency handling, transactional guarantees, retry and failure semantics, and observability for a payments API to ensure correctness and durability under high concurrency and failures.

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Tesla logo
Tesla
Jul 26, 2025, 12:00 AM
Software Engineer
Technical Screen
System Design
2
0

Prevent Double-Spending When Two Users Pay Simultaneously from the Same Account

Context

You are designing a payments service where multiple clients may initiate payments at the same time against a shared account. The system must maintain a correct balance and prevent double-spending even under failures, retries, and high concurrency.

Task

Design the API and backend to ensure correctness and durability. Cover:

  1. Request/response design, including status codes and error semantics.
  2. Idempotency keys and how they are stored/enforced.
  3. Concurrency control strategy (optimistic vs. pessimistic), transactions, and isolation levels.
  4. Consistency guarantees to clients and internally.
  5. Retry strategy and failure handling.
  6. Monitoring, alerting, and observability.
  7. Scaling to very high concurrency and massive request volumes.

Assume a typical service + database architecture. You may make minimal, explicit assumptions as needed.

Solution

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