AI Platform Briefing — Google Vertex AI Launch
Google Cloud introduced Vertex AI on May 18, 2021 to unify AutoML and custom training pipelines, provide managed feature stores, and streamline MLOps deployment on Google Cloud.
Executive briefing: At Google I/O on , Google Cloud announced Vertex AI. The managed platform consolidates model training, data labeling, feature management, and online serving to accelerate regulated enterprise ML adoption.
Key capabilities
- Unified workbench. Vertex AI Workbench merges BigQuery, Dataflow, and managed notebooks to align experimentation with production pipelines.
- Feature Store. A fully managed feature repository enables consistent offline/online features with point-in-time correctness.
- MLOps automation. Vertex Pipelines, Predictions, and Experiments standardize CI/CD for ML, including model registry, versioning, and explainability tooling.
- Responsible AI. Integrated Explainable AI, Vizier, and continuous evaluation services provide monitoring hooks for fairness and drift controls.
Implementation guidance
- Map existing AutoML Tables and custom training workloads into Vertex AI projects to consolidate governance.
- Establish feature engineering standards for ingestion into the Feature Store with lineage tracked in Data Catalog.
- Instrument MLOps pipelines with Vertex Model Monitoring to surface drift metrics required for audit evidence.