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Infrastructure-as-code starter kit

Grid Dynamics has developed and released a cloud-native starter kit for Google Cloud that accelerates the provision of a Machine Learning Platform with end-to-end capabilities, including feature catalog, model repository and CI/CD.

Introduce experiments tracking

A managed Machine Learning Platform on Google Cloud means you have a unified portal to manage experiments with the ability to track model-specific parameters, compare model versions and visualize model key attributes.

Production-ready Machine Learning Platform

Our Machine Learning Platform Starter Kit for Google Cloud provides a full spectrum of ML capabilities: feature store and model repository, experiments tracking, serving layer for batch and real-time inference, model CI/CD.  

The platform starter kit leverages Vertex AI for model development and testing, and provides the environment for runtime.

Use Cases

  • Build an ML Platform from scratch
  • Upgrade an existing ML Platform
  • Introduce new technical features
  • Migrate to the cloud
  • Reduce time-to-market
  • Adopt MLOps best practices


Benefits of a Machine Learning Platform in the cloud


With Infrastructure-as-code, you get to focus on building business critical applications, not on infrastructure provisioning and management.

Managed environment

Fully managed by Google Cloud services and Terraform, infrastructure provisioning takes days, not months. 

Reduced operational costs

The Machine Learning Platform's scalability and modular architecture enables flexible extension of new capabilities with Dataiku or other cloud products.

How It Works

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