# A multi-tenant analytics platform ingests events from 3,000 customer accounts Canonical URL: Domain: Pipeline Design ยท Difficulty: medium ## Problem A multi-tenant analytics platform ingests events from 3,000 customer accounts. One enterprise tenant occasionally bursts to 30 percent of total throughput and slows ingest latency for the other 90 percent of tenants. There is no per-tenant rate cap and no per-tenant lag dashboard. The section names three isolation layers: logical (tenant id stamped on every record, shared infra), resource (each tier gets its own queue or worker pool), and physical (largest tenants get dedicated infrastructure). Plus fair scheduling (round-robin or weighted-fair across tenant-keyed sub-queues). Isolate the noisy tenant by adding the right isolation layer for this platform's tier structure (free, pro, enterprise) and a per-tenant lag monitor that surfaces who is impacting whom. ## Related - [All practice problems](https://datadriven.io/problems) - [Mock interview mode](https://datadriven.io/interview/a-multi-tenant-analytics-platform-ingests-events-from-3000-7f34e373) - [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.