# A live metrics platform serves a real-time consumer dashboard from a streaming aggregation while a p Canonical URL: Domain: Pipeline Design ยท Difficulty: medium ## Problem A live metrics platform serves a real-time consumer dashboard from a streaming aggregation while a producer team prepares a breaking schema change to the underlying event topic. The capstone composes the four intermediate-tier moves: a schema registry that rejects incompatible producer schemas at registration, an expand-contract phase plan to roll out the breaking change, an event_time-bucketed aggregation feeding the consumer, and a watermark plus allowed-lateness budget plus dead-letter sink so late events are caught or quarantined. Add a schema registry between producer and topic with its compatibility mode named, mark the four expand-contract phases on the canvas, route the aggregation by event_time with a named watermark strategy and 60-minute allowed-lateness budget, and add a dead-letter sink for events past the budget. ## Related - [All practice problems](https://datadriven.io/problems) - [Mock interview mode](https://datadriven.io/interview/a-live-metrics-platform-serves-a-real-time-consumer-dashboar-2256d32e) - [System Design Interview Questions](https://datadriven.io/data-engineering-system-design) - [Data Engineering Interview Prep Guide](https://datadriven.io/data-engineer-interview-prep) - [Daily Challenge](https://datadriven.io/daily) --- Source: DataDriven (https://datadriven.io). 100% free data engineering interview prep. Live code execution against Postgres 16, Python 3.11, and Spark sandboxes. No paywall, no premium tier, no signup gate.