Create a new Domino Environment to meet your language and package needs

From the Lab, click Environments.
Click Create Environment.
Name your new Environment and optionally give it a description.
Select whether you want to Start from an existing Environment or Start from a custom base image. See below for more details on custom base images.
Optional: Select the cluster for the Environment.
Set the Environment’s Visibility. Administrators can make the Environment Globally Accessible, which makes it available to all Projects.
Click Create Environment. The Revisions tab for the Environment opens. If you want to customize the Environment by editing the Dockerfile instructions, click Customize before Building and see Edit Environment Definition.

Environment based on Domino Standard Environment

Although Domino comes with only the Domino Standard Environment installed, you can use the Environment images to create a new Domino Environment. This topic describes how to create a new Domino Environment or to customize one.

Select an Environment, choosing the correct Python and R version. Typically, you’ll want to choose the Environment from the latest release of Domino.

Note

Note

Find the appropriate name, description, image URI and pluggable notebook properties for your Environment.

Note

For example, for the Domino Standard Environment you might use:

Title

Domino Standard Environment Py 3.8 R 4.1

URI

quay.io/domino/standard-Environment:ubuntu18-py3.8-r4.1-domino4.6

Description

Ubuntu 18.04
Mini-conda py38_4.9.2
Python 3.8
R 4.1
Jupyter, Jupyterlab, VSCode, Rstudio

Pluggable Workspace Tools (decoded from Environment metadata)

jupyter:
  title: "Jupyter (Python, R, Julia)"
  iconUrl: "/assets/images/workspace-logos/Jupyter.svg"
  start: [ "/opt/domino/workspaces/jupyter/start" ]
  httpProxy:
    port: 8888
    rewrite: false
    internalPath: "/{{ownerUsername}}/{{projectName}}/{{sessionPathComponent}}/{{runId}}/{{#if pathToOpen}}tree/{{pathToOpen}}{{/if}}"
    requireSubdomain: false
  supportedFileExtensions: [ ".ipynb" ]
jupyterlab:
  title: "JupyterLab"
  iconUrl: "/assets/images/workspace-logos/jupyterlab.svg"
  start: [  /opt/domino/workspaces/jupyterlab/start ]
  httpProxy:
    internalPath: "/{{ownerUsername}}/{{projectName}}/{{sessionPathComponent}}/{{runId}}/{{#if pathToOpen}}tree/{{pathToOpen}}{{/if}}"
    port: 8888
    rewrite: false
    requireSubdomain: false
vscode:
  title: "vscode"
  iconUrl: "/assets/images/workspace-logos/vscode.svg"
  start: [ "/opt/domino/workspaces/vscode/start" ]
  httpProxy:
    port: 8888
    requireSubdomain: false
rstudio:
  title: "RStudio"
  iconUrl: "/assets/images/workspace-logos/Rstudio.svg"
  start: [ "/opt/domino/workspaces/rstudio/start" ]
  httpProxy:
    port: 8888
    requireSubdomain: false

Create a new Domino Compute Environment.
- See Environment management for how to create and manage Environments. This section also includes information about how to customize your Environment with Docker commands or pre-run scripts.
Update your Domino AMI (not required for non-cloud).
- After you’ve created a compute Environment with a new base image, work with your administrator to update your Domino’s AMI (or if not on AWS, the GCP or Azure equivalent) by caching the new image. As Domino spins up and down new executors, if your new image is not in the AMI, it must pull that image onto the executor the first time it starts up. This can cause a ~10 minute delay for starting Workspaces on new executors. Follow the procedure to snap and update your AMI.

Environment based on custom images

Enter the custom Docker or container image URI in the FROM line. For example, registry.hub.docker.com/library/python:3.8-slim.

Note

Automatically compatible environment creation

What is automatic compatibility?

Domino:

Validates that automatic compatibility pre-requisites are in the image.
Adds the dependencies required for use with Domino in an isolated location.
Builds the Environment.

The functionality of your image remains untouched. Code and tools that run using the image in Domino will work when using the image outside of Domino and vice versa. The Environment is just like any other Domino Environment.

Note

Copy an Environment

In the navigation pane of the Lab, click Environments.
Click the name of an Environment.
Click Duplicate Environment to create a clone.

Hide/Archive an Environment

In the navigation pane of the Lab, click Environments.
Click the name of an Environment.
If you have permission, click Archive Environment.

Archiving an Environment does not break reproducibility and executions based on that Environment will still run. See Sunset Environments in the Admin guide to learn more about archiving Environments.

Example: Create a New Environment from a Domino base image

Although Domino comes with only the Domino Standard Environment installed, you can use the environment images to create a new Domino Environment. This topic describes how to create a new Domino Environment or to customize one.

Select an environment, choosing the correct Python and R version. Typically, you’ll want to choose the environment from the latest release of Domino.

Note

Note

Find the appropriate name, description, image URI and pluggable notebook properties for your environment.

Note

For example, for the Domino Standard Environment you might use:

Title

Domino Standard Environment Py 3.8 R 4.1

URI

quay.io/domino/standard-environment:ubuntu18-py3.8-r4.1-domino4.6

Description

Ubuntu 18.04
Mini-conda py38_4.9.2
Python 3.8
R 4.1
Jupyter, Jupyterlab, VSCode, Rstudio

Pluggable Workspace Tools (decoded from environment metadata)

jupyter:
  title: "Jupyter (Python, R, Julia)"
  iconUrl: "/assets/images/workspace-logos/Jupyter.svg"
  start: [ "/opt/domino/workspaces/jupyter/start" ]
  httpProxy:
    port: 8888
    rewrite: false
    internalPath: "/{{ownerUsername}}/{{projectName}}/{{sessionPathComponent}}/{{runId}}/{{#if pathToOpen}}tree/{{pathToOpen}}{{/if}}"
    requireSubdomain: false
  supportedFileExtensions: [ ".ipynb" ]
jupyterlab:
  title: "JupyterLab"
  iconUrl: "/assets/images/workspace-logos/jupyterlab.svg"
  start: [  /opt/domino/workspaces/jupyterlab/start ]
  httpProxy:
    internalPath: "/{{ownerUsername}}/{{projectName}}/{{sessionPathComponent}}/{{runId}}/{{#if pathToOpen}}tree/{{pathToOpen}}{{/if}}"
    port: 8888
    rewrite: false
    requireSubdomain: false
vscode:
  title: "vscode"
  iconUrl: "/assets/images/workspace-logos/vscode.svg"
  start: [ "/opt/domino/workspaces/vscode/start" ]
  httpProxy:
    port: 8888
    requireSubdomain: false
rstudio:
  title: "RStudio"
  iconUrl: "/assets/images/workspace-logos/Rstudio.svg"
  start: [ "/opt/domino/workspaces/rstudio/start" ]
  httpProxy:
    port: 8888
    requireSubdomain: false

Create a new Domino Compute environment.
- See Environment Management for how to create and manage environments. This section also includes information about how to customize your environment with Docker commands or pre-run scripts.
Update your Domino AMI (not required for non-cloud).
- After you’ve created a compute environment with a new base image, work with your administrator to update your Domino’s AMI (or if not on AWS, the GCP or Azure equivalent) by caching the new image. As Domino spins up and down new executors, if your new image is not in the AMI, it must pull that image onto the executor the first time it starts up. This can cause a ~10 minute delay for starting workspaces on new executors. See here for the procedure to snap and update your AMI.

Create an Environment

Environment based on Domino Standard Environment

Environment based on custom images

What is automatic compatibility?

Copy an Environment

Hide/Archive an Environment

Example: Create a New Environment from a Domino base image