Infrastructure-as-code starter kit

Grid Dynamics has built and published a cloud-native starter kit on AWS Marketplace that accelerates the development and deployment of a modernized Machine Learning Platform. The starter kit enables rapid provisioning of the Machine Learning Platform, provides a CI/CD framework and sample models for reference.

Introduce experiments tracking

A managed Machine Learning Platform on AWS 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 AWS 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 Sagemaker for model development, Mlflow for experiments tracking, S3 as a feature store, EKS or Sagemaker for real-time serving and Amazon EMR (Elastic MapReduce) for batch serving. CI/CD automation is implemented on top of CodeBuild and Lambda, and platform deployment is fully automated on CloudFormation.

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 DataOps 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 AWS CloudFormation and AWS services, 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 serving on Amazon EKS (Elastic Kubernetes Service),or integration with 3rd party ML services.

How It Works

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