Practical notes on Feature stores for real-time ML

What to measure first

Log latency percentiles, token counts, and failure modes before changing models. Averages hide the pain users feel.

Minimal code check

Start with a tiny reproducible script so every experiment is comparable.

import time
t0 = time.time()
# run inference
print('seconds', time.time() - t0)

Ship checklist

Pin versions, add eval gates, and name an owner for the first week in production.

Takeaway: Measure, baseline, then optimize the bottleneck you can prove.