Tag: vertex ai

A production-focused Vertex AI post on turning raw data, BigQuery features, online feature serving, model endpoints, monitoring, and retraining into one governed ML loop instead of another platform checklist.

Outcome: Defined a concrete Vertex AI feature-serving loop with source contracts, BigQuery feature views, point-in-time training exports, endpoint serving rules, monitoring thresholds, and retraining triggers.

A Vertex AI architecture map for teams that need to decide which Google Cloud AI services belong in the ML lifecycle, where ownership changes hands, and which older assumptions are now unsafe.

Outcome: Gave teams an operating contract for using Vertex AI across data, features, training, deployment, monitoring, and generative AI without confusing a product menu for a production ML system.