# Manage pipeline images

> Manage pipeline images - Create, rebuild, and delete reusable container images for pipelines in
> Registry.

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 `2026-10-09T14:18:51.481533+00:00` (UTC).

## Primary page

- [Manage pipeline images](https://docs.datarobot.com/ja/docs/workbench/registry/pipelines/pipeline-images.html.md): Full documentation for this topic (Markdown sidecar).

## Sections on this page

- [Review an image](https://docs.datarobot.com/ja/docs/workbench/registry/pipelines/pipeline-images.html.md#review-an-image): In-page section heading.
- [Create an image](https://docs.datarobot.com/ja/docs/workbench/registry/pipelines/pipeline-images.html.md#create-an-image): In-page section heading.
- [次のステップ](https://docs.datarobot.com/ja/docs/workbench/registry/pipelines/pipeline-images.html.md#next-steps): In-page section heading.

## Documentation content

Images are reusable container environments for pipelines. An image carries the third-party Python packages a pipeline needs (for example, scikit-learn, pandas, or scipy) and can be shared across pipelines and runs. Images live on the Images tab, alongside the pipeline list.

The following table describes the columns on the Images list.

| 列 | 説明 |
| --- | --- |
| 画像 | The image name and a status indicator for the latest build. |
| バージョン | The current image version. |
| 作成 | When the image was created. |

Expand the for an image in the list to rebuild or delete it.

## Review an image

Open an image to review package dependencies, build status, and build logs.

The following table describes the fields on the image page.

| フィールド | 説明 |
| --- | --- |
| ステータス | Build state of the image (for example, Ready). |
| 作成 | When the image was created. |
| Pythonのバージョン | Python runtime for the image, or Platform default. |
| GPU | Whether the image includes GPU support (for example, Disabled). |
| packages | Third-party packages pip-installed into the image. |
| ログ | Output from the image build. Refresh, copy, or download from the icons on the pane. |

> [!NOTE] 備考
> A run cannot start until the selected image is ready. If a pipeline was created with an image that is still building, wait for the build to finish on the Images tab before running.

## Create an image

On the Images tab, click + Add image to define a container environment that pipelines can share.

1. Enter a Name and, optionally, a Description .
2. In the YAML editor, list the Python packages to pip-install. UncommentpythonVersionorgpuonly if a different Python version or a GPU image is required. image.yamlpackages:-"scikit-learn>=1.3"-"numpy>=1.26"# pythonVersion: "3.12"# gpu: false
3. 作成をクリックします。

The image builds in the background and appears in the Images list. A run cannot start until Status is Ready.

## 次のステップ

After managing images, attach one to a new pipeline or run a pipeline with an existing image.

- Add a pipeline : Select an existing image or create a new one when adding a pipeline.
- Run and schedule pipelines : Choose an image when starting a run.
- View and manage pipelines : Open a pipeline that uses the image.