_index

---
stage: ModelOps
group: MLOps
info: To determine the technical writer assigned to the Stage/Group associated with this page, see <https://handbook.gitlab.com/handbook/product/ux/technical-writing/#assignments>
title: MLOps
---

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- Tier: Free, Premium, Ultimate
- Offering: GitLab.com, GitLab Self-Managed, GitLab Dedicated

{{< /details >}}

GitLab Machine Learning Operations (MLOps) is set of tools designed to help with
your machine learning workflows.

GitLab MLOps features include:

- Model registry: Manage your machine learning models, along with associated metadata such
  as parameters, performance metrics, artifacts, and logs. For more information, see
  [model registry](model_registry/_index.md).
- Model experiments: Track and manage machine learning experiments in GitLab.
  An experiment is a collection of comparable model candidates, which are variations of the training of a
  machine learning model. For more information, see [model experiments](experiment_tracking/_index.md).

## GitLab MLOps Python client

GitLab offers a Python client to interact with the GitLab MLOps features.

For details, see the [GitLab MLOps Python client](https://gitlab.com/gitlab-org/modelops/mlops/gitlab-mlops).