Price Tracking Service

Difficulty: Medium

What It Tests

Periodic data collection, change detection, time-series storage, and alerting at scale.

Topics Covered

• Message Queues & Async Processing
• Database Design: SQL vs NoSQL
• Time Series Databases
• Job Scheduling & Background Processing
• Ad Aggregation Pipelines

Hello Interview Breakdown

Read the full Hello Interview breakdown →

Video Walkthroughs

• System Design: Price Drop Tracker (FAANG Senior Engineer) →
• Design a Price Drop Tracker — DB Design & Camelcamelcamel Deep Dive →

Approach Hints

• Scheduled scrape jobs per product (cron-based with random jitter to avoid thundering herd against retailers)
• Store price history as time-series data; compare new price to last known price to detect drops
• Publish price-drop events to Kafka and fan out to alert workers that notify users via email/push
• Rate-limit notifications per user (max 1 alert per product per day) and allow users to set threshold percentages