> ## 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.

# Setting up a cloud workstation

Cloud workstations are personal development environments hosted on Anaconda Platform. Each workstation comes with a persistent disk, so your data persists across restarts and hibernation.

To create a workstation, open **Workstations** and click **Add workstation**:

<Frame>
  <img src="https://mintcdn.com/anaconda-29683c67/VD0yQ0tXYWIdTsBU/images/platform/plat_add_workstation_button.png?fit=max&auto=format&n=VD0yQ0tXYWIdTsBU&q=85&s=c8f27adc233024aab8984ad273a8bdc6" alt="The Workstations page with the Add workstation button spotlighted" width="1866" height="763" data-path="images/platform/plat_add_workstation_button.png" />
</Frame>

In the creation dialog, configure the following:

<Frame>
  <img src="https://mintcdn.com/anaconda-29683c67/VD0yQ0tXYWIdTsBU/images/platform/plat_workstation_with_image.png?fit=max&auto=format&n=VD0yQ0tXYWIdTsBU&q=85&s=e09cb3271dedf8d49cdff7ebf8b2bfe7" alt="The Create a new workstation dialog showing the Name, Owner, Image, and resource fields" width="1866" height="1035" data-path="images/platform/plat_workstation_with_image.png" />
</Frame>

* **Name**: A name for the workstation, useful for telling multiple workstations apart.
* **Owner**: The user the workstation is assigned to. The user must have been invited to the platform first.
* **Image**: The container image backing the workstation. For dependency options, see [Managing dependencies](/docs/platform/guides/compute/managing-dependencies).
* **Auto-hibernate**: When the workstation shuts down automatically after a period of inactivity.
* **Resources**: The CPU, memory, disk, and GPU allocated to the workstation. If no compute pool in your cluster can satisfy the requirements you enter, the dialog warns you before it creates the workstation.
* **Shared memory**: The size of the workstation's `/dev/shm` in-memory filesystem. Increase this for libraries that use shared memory heavily, such as multi-worker PyTorch data loading.

Click **Create**. The workstation takes a few minutes to come online.

<Tip>
  Workstations with greater CPU and memory capacity deliver better performance. If you handle large datasets or demanding algorithms, provision adequate resources, such as a minimum of four CPU cores and 16 GB of RAM. If cost is a concern, [cost reporting](/docs/platform/guides/monitor/using-cost-reports) can help you understand the financial impact.
</Tip>

## Workstation lifecycle

On the **Workstations** page, you can see a list of provisioned workstations. The **Status** indicator shows the state of each workstation:

* **Green**: The workstation is active and ready to use.
* **Spinner**: The workstation is starting or stopping.
* **Gray**: The workstation has been hibernated (shut down) and is not consuming resources. An admin or the owner restarts it manually to make it active again.

An admin can delete or hibernate a workstation by selecting an action in the rightmost column of the workstation list.

## Connecting and working

For instructions on connecting to a workstation, see [Connecting to a cloud workstation](/docs/platform/guides/develop/connecting-to-a-cloud-workstation).

<Note>
  A workstation is not meant for long-term persistent data storage. Push your code to a repository regularly, and avoid relying on datasets that exist only on a workstation.
</Note>