Blog / Track and Manage the Lifecycle of ML Models with Valohai’s Model Registry
Track and Manage the Lifecycle of ML Models with Valohai’s Model Registry

Track and Manage the Lifecycle of ML Models with Valohai’s Model Registry

Tarek Oraby

Valohai is happy to announce the availability of the Model Registry, a new feature that enables teams to manage and track the lifecycle of models from development to deployment. The Model Registry provides a single source of truth for models and their versions, making it easier to collaborate and share models across teams.

What is Valohai's Model Registry?

The Model Registry is a centralized hub for managing ML models' versioning and metadata. It provides a systematic way to track different versions of models along with details like their parameters, performance metrics, and approval status.

The view of model versions and metrics in Valohai's Model Registry. The view of model versions and metrics in Valohai's Model Registry.

The Model Registry enables you to:

  • Manage model versions and facilitate their promotion for production readiness.
  • Utilize single or multiple files to represent a "model".
  • Provide comprehensive descriptions, use cases, explanations, and deployment usage instructions.
  • Manage model states (approved, pending, rejected) for seamless workflow management.
  • Trace the model creation process for transparency and reproducibility.

The view of a model card in Valohai's Model Registry. The view of a model card in Valohai's Model Registry.

Benefits of using Valohai’s Model Registry include:

  • Better collaboration and coordination: the Model Registry enhances team collaboration by providing a shared, transparent view of model details and version history. By enabling the naming of models and adding detailed descriptions of what they do, Model Registry fosters alignment and efficiency among ML teams.
  • Reproducibility and debugging: when things go wrong with a model, the Model Registry enables users to easily trace the data, code, and environment settings used to generate the model, facilitating debugging and issue resolution.
  • Governance and approval mechanisms: Valohai's Model Registry enables organizations to implement policies and workflows for approving and deploying models, reducing the risk of using outdated or unauthorized models in production.
  • Monitoring and accountability: the Model Registry provides visibility into the model deployment lifecycle, enabling organizations to track and audit model changes and ensure compliance with regulatory requirements.

Leverage Valohai’s Model Registry to take the guesswork out of model management and bring unmatched clarity to your machine-learning operations.

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