nomlops3.md

Challenge	Automation solution	Keep It Simple Solution	Complexity needed if …
Training-Serving Skew, where differences crop up between training and serving stacks	Feature Store	Transform Pattern	Features injected server-side
Clients are interested in a capability that involves multiple steps, only one of which is the ML model	ML Pipelines	Stateless Serving Function	Cascade of ML models
The incoming data changes characteristics	Continuous evaluation	Scheduled evaluation	Robust mitigation available
The correct answer changes over time	Continuous training	Systematic triggers	Adaptive system
Model fairness issues arise	Mumbo Jumbo	Manual sliced evaluations and other checks	Need to turn off
Parts of the system aren’t changed when new code is checked in	CI/CD	From-scratch builds	Large repo, frequent model changes
Need to be able to troubleshoot old results	Model registry, Data registry	Version control all deployed artifacts	Hundreds of models