Selected Template
Managed Experiment Tracking with MLFlow
The template takes you one step toward reproducibility with your personalized instance.
An open-source package that manages the complete ML lifecycle including experimentation, reproducibility, deployment, and central model registry.
Use MLFlow to better track ML experiments.
Benefits of Managed Experiment Tracking with MLFlow through the Aliz Intelligence Platform
Quick start on GCP with a ready-to-use code and project
Track models with Managed Experiment Tracking and Model Registry service
Deploy model within Platform infrastructure for seamless and trouble free operation
IAM: manage roles and permissions on user and domain level, or access with service account
Manage multiple environments (dev, testing, staging, etc.), trace activity and changes
About the solution
What are the benefits of Managed Experiment Tracking with MLFlow?
Compliance and transparency
The Managed Experiment Tracking with MLFlow blueprint includes industry best practices in the form of ready-to-use codes or templates delivered to you, on your infrastructure, through seamless deployment for sustainable quality.
Composable business
The platform allows you to standardize workflows. Developing the models with maximum efficiency will not interfere with integration and will manage the risk of a lower ROI due to productizing and integration.
Effortless quality assurance
Applying best practices in production requires continual improvement and support. Leveraging on the blueprint repository of Aliz Intelligence Platform ensures that the technology is always up to date.
What’s under the hood?
Things you don't need to care about.
Enterprise ready
This out-of-the-box set-up is enterprise ready and powered by Terraform.