Why this clean-architecture-zh pattern gets slow in production: a source-level explanation
Short version: clean-architecture-zh needs almost no tuning at small and medium scale — the point where it starts to hurt is much further out than most people assume. Full measurements below.
The first thing was to collapse the variables. We were changing config and upgrading the version at the same time, and afterwards nobody could say which change caused what. We rolled back to moving one variable at a time, re-ran three times, and only then did the curve settle. Tedious, but not skippable.
-- The query that broke: a full scan over 20M rows. -- A composite index took P99 from 1.8s down to 42ms. SELECT id, title, created_at FROM posts WHERE community_id = ? AND status = 1 ORDER BY score DESC LIMIT 20;
What genuinely surprised me was the tail. The average looked great while P99 jumped by an order of magnitude past some threshold. The cause was not clean-architecture-zh itself but our upstream connection reuse — the load test traffic was too clean and hid the long-tail requests.
We also fixed monitoring along the way: replaced average-based alerts with percentiles and split them per endpoint. False alerts dropped by about seventy percent and the on-call rotation visibly cheered up.