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The Counter That Is Always Low
Pull up the evidence one item at a time, commit to a diagnosis, and only then see the schedule that actually ran.
What was reported
We count feature-flag evaluations in memory and scrape the map every 15 seconds. In the test suite the count is exact. In production it is always low and never high — yesterday the request log had 1,204,338 evaluations and the counter reported 1,199,871. That is a 0.37% shortfall. Nothing throws, nothing is logged, and the gap gets wider on our busiest hosts.
1# metrics.py — one process, 8 worker threads, CPython 3.122from collections import defaultdict3 4counts = defaultdict(int)5 6def record(flag: str) -> None:7 counts[flag] += 1 # read, add, store — not one operationEvidence
Nothing here is labelled as relevant. Some of it is not.