# Lifecycle management

> Lifecycle management - Lifecycle management provides tools and a robust, repeatable process to scale
> models and manage the lifecycle of models in production environments.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-04-24T16:03:56.573197+00:00` (UTC).

## Primary page

- [Lifecycle management](https://docs.datarobot.com/en/docs/classic-ui/mlops/manage-mlops/index.html): Full documentation for this topic (HTML).

## Related documentation

- [Classic UI documentation](https://docs.datarobot.com/en/docs/classic-ui/index.html): Linked from this page.
- [MLOps](https://docs.datarobot.com/en/docs/classic-ui/mlops/index.html): Linked from this page.
- [deployment considerations](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/index.html#feature-considerations): Linked from this page.
- [Deployment inventory (Deployments page)](https://docs.datarobot.com/en/docs/classic-ui/mlops/manage-mlops/deploy-inventory.html): Linked from this page.
- [Manage deployments](https://docs.datarobot.com/en/docs/classic-ui/mlops/manage-mlops/actions-menu.html): Linked from this page.
- [Replace deployed models](https://docs.datarobot.com/en/docs/classic-ui/mlops/manage-mlops/deploy-replace.html): Linked from this page.
- [Set up Automated Retraining policies](https://docs.datarobot.com/en/docs/classic-ui/mlops/manage-mlops/set-up-auto-retraining.html): Linked from this page.

## Documentation content

# Lifecycle management

Machine learning models in production environments have a complex lifecycle, and the use and value of models requires a robust and repeatable process to manage that lifecycle. Without proper management, models that reach production may deliver inaccurate data, poor performance, or unexpected results that can damage your business’s reputation for AI trustworthiness. Lifecycle management is essential for creating a machine learning operations system that allows you to scale many models in production.

The following sections describe how to manage models in production. Be sure to review the [deployment considerations](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/index.html#feature-considerations) before proceeding.

| Topic | Description |
| --- | --- |
| Deployment inventory (Deployments page) | Coordinate deployments and view deployment inventory. |
| Manage deployments | Understand the actions you can take with deployments. |
| Replace deployed models | Replace the model used for a deployment. |
| Set up Automated Retraining policies | Configure retraining policies to maintain model performance after deploying. |