Code Room
System designHard
Question
Design a time-series storage engine for metrics/observability: ~5 million unique series, ~2 million samples/sec ingested (timestamp + float per series), queries that scan a few series over a time range plus dashboard aggregations, and retention that keeps raw data 15 days but rolled-up data for a year. How do you ingest, store, compress, and query this efficiently while keeping cost down?
What a strong answer looks like
Clarify scale and constraints first. Propose a clean component breakdown, then go deep on the hard parts — data model, bottlenecks, consistency, failure modes — and name the trade-offs you are making.
Learn the concepts
Loading whiteboard…
Run or narrate your approach, then ask the coach.