> ## Documentation Index
> Fetch the complete documentation index at: https://anaconda.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Generating custom Anaconda installers

As an Data Science & AI Workbench Administrator, you can [create custom environments](#creating-an-environment). These environments include specific packages and their dependencies. You can then [create a custom installer](#creating-a-custom-installer-for-an-environment) for the environment, that can be shipped to HDFS and used in Spark jobs.

Custom installers enable IT and Hadoop administrators to maintain close control of a Hadoop cluster while also making these tools available to data scientists who need Python libraries. They provide an easy way to ship multiple custom Anaconda distributions to multiple Hadoop clusters.

## Creating an environment

1. Open the <Icon icon="circle-user" iconType="light" /> **My Account** dropdown menu and select *Admin Console*.

2. Select <Icon icon="laptop" iconType="light" /> **Environments** from the left-hand navigation.

3. Click <Icon icon="plus" iconType="light" /> **Create**, give the environment a unique name, and then click **Save**.

   <Note>
     Environment names can contain alphanumeric characters and underscores only.
   </Note>

4. Select the channel you want to choose packages from, then select the specific packages—and version of each—you want to include in the installer.

5. Click <Icon icon="floppy-disk" iconType="light" /> **Save** to create the environment. Workbench resolves all the package dependencies and displays the environment in the list.

   <Note>
     If there is an issue resolving the dependencies, you'll be notified and prompted to edit the environment.
   </Note>

You can now use the environment as a basis for creating additional versions of the environment or other environments.

### Editing an existing environment

1. Click on an environment name to view details about the packages included in the environment, then click **Edit**.
2. Change the channels and/or packages included in the environment, and enter a version number for the updated package before clicking **Save**. The new version is displayed in the list of environments.

## Creating a custom installer for an environment

Select the environment in the list, click <Icon icon="plus" iconType="light" /> **Create installer**, and then select the type of installer you want to create. Workbench creates the installer and displays it in the <Icon icon="file-zipper" iconType="light" /> **Installers** list.

<Note>
  * *If you created a management pack*: Install it on your Hortonworks HDP cluster and add it to your local Ambari server to make it available to users. For more information, see [this blog post about generating custom management packs](https://www.anaconda.com/blog/self-service-open-data-science-custom-anaconda-management-packs-hortonworks-hdp).
  * *If you created a parcel*: Install it on your CDP cluster to make it [available to users](https://docs.cloudera.com/cdp-private-cloud-base/latest/index.html), or directly download the parcel onto your CDP cluster [as described here](/docs/data-science/latest/data-science-workflows/installers).
</Note>

Use the icons at the top of the page to manage your environment. You can edit, duplicate, delete, and view logs and resolved packages for the selected environment.

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