Infrastructure for model work.
WHAT IT SHOULD PROVIDE
Access to data Environments for experimentation Training execution, including on larger hardware Experiment tracking A model registry Deployment and serving Monitoring
WHAT TO BUILD FIRST
Nothing. Deliver one model manually, and see what hurts.
WHY
Platforms built before use encode assumptions that turn out wrong.
WHAT TO ADD FIRST, USUALLY
Reproducible training, and experiment tracking.
WHAT TO ADD NEXT
Automated deployment and monitoring.
WHAT MANAGED SERVICES PROVIDE
Most of this, without building it.
WHAT THEY COST
Cost, and coupling to a provider.
WHAT TO WEIGH
Your team's size against operational burden.
WHY THAT MATTERS MOST FOR SMALL TEAMS
A platform requiring more operation than you can sustain degrades and is abandoned.
WHAT TO STANDARDISE
Project structure How data is accessed How models are packaged How deployment happens
WHY
So models from different people work the same way.
WHAT TO AUTOMATE
Everything performed manually more than a few times.
WHAT TO MEASURE
Time from idea to production.
