Managed Service for MLflow
A fully managed service for an industry-leading tool for managing the machine learning lifecycle.
The service is provided free of charge and is at the Preview stage.
Zero infrastructure maintenance
Nebius offers MLflow, an industry-leading tool for optimizing the ML lifecycle, as a fully managed and ready-to-work cloud solution. This enables you to deliver production-ready models faster without having to worry about server provisioning.
Transparent ML pipeline
MLflow collects and organizes the metadata of your model training, making your ML pipeline more transparent and visible. That allows your ML team to control the progress and apply relevant changes with the highest level of precision.
Improved collaboration
Developing ML models creates a huge amount of information and assets that must be accessible to various stakeholders. MLflow provides efficient tools for organizing and easily sharing them across the team.
Use cases
Experiment tracking
Ensure predictability and reproducibility of all your ML endeavors with the MLflow Tracking module that collects, stores and visualizes every run of your ML models.
Model management
Simplify your model management routines with the MLflow Model Registry that easily store and deliver model files across different stages of the ML pipeline.
How it works
How it works
Service features
MLflow Tracking
Gathers data from your training cluster and lets you track and monitor the experiment’s progress in detail.
MLflow Model Registry
Provides your team with a shared model store and delivers a granular representation of models' parameters, such as versions, lineage and production-ready statuses.
Quick start
To start tracking, you just need to copy a couple of lines of code and paste them into your training cluster environment.
Seamless integration with storage
Use Object Storage for simple and cost-efficient model storing.
Easy management
Utilize GUI, CLI, IDE or Jupyter Notebook to access MLflow functionality.
We take care of most of the maintenance
Questions and answers about Managed MLflow
What is MLflow?
What is MLflow?
MLflow is an open-source platform, purpose-built to assist machine learning practitioners and teams in handling the complexities of the machine learning process. MLflow focuses on the full lifecycle for machine learning projects, ensuring that each phase is manageable, traceable and reproducible.
What version of MLflow do you support?
What version of MLflow do you support?
What MLflow components are currently available?
What MLflow components are currently available?
How do you make backup for the service?
How do you make backup for the service?
Do you provide SLA for the product?
Do you provide SLA for the product?
Should I configure a virtual machine to get this product running?
Should I configure a virtual machine to get this product running?
Is Managed Services for MLflow a paid service?
Is Managed Services for MLflow a paid service?