Standardize How You Train on Vertex AI — No More One-off Notebooks.
The Vertex AI Training Factory Playbook turns ad-hoc experiments into a governed, repeatable training pipeline: serverless training jobs, hyperparameter tuning, MLOps, and cost controls baked in from day one.
What This Playbook Actually Delivers
This is not a generic “how to use Vertex AI” tutorial. The Training Factory Playbook gives you a reusable blueprint to industrialize model training across teams, projects, and business units.
Serverless Training Patterns
Opinionated templates for CustomJob, HyperparameterTuningJob, and Training Pipelines that your teams can reuse instead of starting from zero every time.
Framework Coverage
Patterns for TensorFlow, PyTorch, scikit-learn, and XGBoost — mapped to prebuilt or custom containers so data scientists can focus on training code, not infra wiring.
MLOps Integration
Hooks into Vertex AI Model Registry, experiment tracking, and CI/CD so models don’t get stuck in notebooks or forgotten buckets.
Cost & Governance Guardrails
Opinionated defaults for machine types, GPUs, and quotas that protect you from surprise bills while still letting teams run serious workloads.
Who This Is For
The Vertex AI Training Factory is designed for organizations that already use Google Cloud — or plan to — and need to move beyond “one senior engineer who knows how it all works.”
- CIOs & CTOs who want training to be a platform capability, not tribal knowledge.
- Heads of Data / ML who are tired of teams copy-pasting brittle scripts.
- Cloud Center of Excellence (CCoE) teams who need standards and guardrails.
- Enterprises migrating from DIY GKE or on-prem training to managed Vertex AI.
What’s Inside the Playbook
Every playbook ships with a concrete package of assets you can deploy or adapt inside your environment.
- Reference architectures for serverless training on Vertex AI.
- Template repositories for training jobs in at least two frameworks (e.g., PyTorch and TensorFlow).
- Sample Training Pipeline definitions that chain data prep, training, and model registration.
- Guides for choosing prebuilt vs. custom containers and packaging training code.
- Checklists for IAM, VPC Service Controls, CMEK, and data isolation.
Engagement Options
You can consume this playbook as a blueprint, or engage a Vapor Cloud Digital Leader (VCDL) for full implementation.
- Blueprint Only: You take the assets and implement with your internal team.
- Guided Implementation: We pair with your team to land the first use cases and train your people.
- Managed Training Factory: Ongoing collaboration where we help you run and evolve the platform.