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Design real-time crypto prices homepage

Last updated: Mar 29, 2026

Quick Overview

This question evaluates system design competency for real-time, low-latency data pipelines and client fanout for a crypto prices homepage, testing skills in data ingestion and normalization, streaming updates, API design, caching and storage, scalability, multi-region reliability, and monitoring.

  • hard
  • Coinbase
  • System Design
  • Software Engineer

Design real-time crypto prices homepage

Company: Coinbase

Role: Software Engineer

Category: System Design

Difficulty: hard

Interview Round: Onsite

Design a system that powers a “crypto explore/home” page (like an exchange’s market page) that: - Shows a list of crypto assets (e.g., BTC, ETH, SOL, …) - Displays **near real-time price updates** (and optionally 24h change, volume, etc.) - Updates many concurrent clients efficiently (web + mobile) Assume you have access to upstream market data (from exchanges/market makers/internal pricing service) that produces frequent ticks. ### What to cover - Requirements (latency, freshness, accuracy, ordering) - APIs for initial page load and live updates - Data ingestion/normalization and internal price computation - Fanout strategy to clients (WebSockets/SSE/push) - Storage, caching, and historical needs (optional) - Scalability, multi-region, reliability, and monitoring

Quick Answer: This question evaluates system design competency for real-time, low-latency data pipelines and client fanout for a crypto prices homepage, testing skills in data ingestion and normalization, streaming updates, API design, caching and storage, scalability, multi-region reliability, and monitoring.

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Coinbase logo
Coinbase
Jan 22, 2026, 12:00 AM
Software Engineer
Onsite
System Design
7
0
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Design a system that powers a “crypto explore/home” page (like an exchange’s market page) that:

  • Shows a list of crypto assets (e.g., BTC, ETH, SOL, …)
  • Displays near real-time price updates (and optionally 24h change, volume, etc.)
  • Updates many concurrent clients efficiently (web + mobile)

Assume you have access to upstream market data (from exchanges/market makers/internal pricing service) that produces frequent ticks.

What to cover

  • Requirements (latency, freshness, accuracy, ordering)
  • APIs for initial page load and live updates
  • Data ingestion/normalization and internal price computation
  • Fanout strategy to clients (WebSockets/SSE/push)
  • Storage, caching, and historical needs (optional)
  • Scalability, multi-region, reliability, and monitoring

Solution

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