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To create a workspace, you need to select few options including workspace name, cluster, resource, image and few advanced settings.

Create a new Workspace on VESSL

Enjoy your interactive works

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Workspace name

Once you start to create a new workspace, the default workspace name will be randomly generated. Specify a good name to remember.

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Cluster

You can choose between VESSL Cloud, which is a cluster managed by VESSL AI, or a custom cluster that you register yourself. (See configure organization cluster for more details.) VESSL Cloud is always hosted on a cloud vendor’s server, while the custom cluster can be hosted either on a cloud server or on an on-premises server.
We support the following integrations:
  • AWS EKS
  • GCP GKE

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Resource

Choose the type of resource that the container will use. Select the resource among the dropdown option or specify the requirements manually.

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Max runtime

Specify the max runtime for this workspace. After max runtime, workspace will be automatically stopped.
For the Enterprise plan, Organization admin can limit the max runtime that users can input.

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Image

You can choose the Docker image that the workspace container will use. There are two types of images: the Managed Image and the Custom Image. Select the Docker image type that you want to run on the workspace container.
  • Managed Image
  • Custom Image
For the Managed Image, you can simply select such an option, then the image managed by VESSL AI will be used in default. You can run Jupyter services on the managed image.
Debian based images are compatible.

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Volumes

Volumes enable you to bring data into your workspace and provide persistent storage solutions for your development environment. They are essential for accessing datasets, code repositories, and other files needed for your interactive work.

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Import Volumes

Import volumes download data from external sources into your workspace container at startup. This is useful for:
  • Code: Pull code from version control systems such as GitHub, GitLab, or BitBucket.
  • Dataset and Model: Retrieve datasets or models defined in VESSL Dataset or VESSL Model Registry.
  • Hugging Face: Fetch datasets or models from Hugging Face repositories.
  • Files: Incorporate files from VESSL Storage volumes.
  • Object Storage: Download data directly from cloud services like AWS S3 or Google Cloud Storage.

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Mount Volumes

Mount volumes provide persistent storage solutions, directly attaching to your workspace container for ongoing data access. They are particularly valuable for:
  • Dataset: Attach datasets predefined in VESSL Dataset for direct use in the container.
  • VESSL Storage: Mount volumes from VESSL Storage for persistent file access across workspace sessions.
  • External Storage: Connect to external storage solutions like AWS S3 or Google Cloud Storage.
  • On-premises Storage: Connect to on-site data storage solutions using Network File System (NFS) or host path configurations (custom clusters only).
  • GCS Fuse: Integrate Google Cloud Storage using GCS Fuse for seamless data accessibility.
Unlike runs, workspaces don’t typically use export volumes since the /root directory provides built-in persistence for your work.

Learn more about VESSL Storage

Explore VESSL’s storage system for managing your data and volumes.

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Advanced setting

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Disk

You can specify the disk size to use in your container. This will be the request storage size of your PVC. The disk size cannot be changed once the workspace is created.
Disk size can be ignored in a custom cluster due to limitation of kubernetes. (official docs)

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Port

You can customize port settings. By default, 8888 (jupyter) and 22 (ssh) are exposed.

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Initialization (init) script

Init script is a shell script that runs every time the workspace starts. Because /root is the only persistent directory, packages you installed outside the home directory may reset on stop and start. In this case, you can fill init script with install commands such as apt-get update && apt-get install ripgrep -y.