User acceptance testing

You can use this user acceptance testing (UAT) list as a guide to check for issues after you install or upgrade Domino. You can also use this list to help establish your instance’s baseline functionality before an upgrade. Each item in the list pertains to a Domino feature and its expected behavior. Treat these items as suggested tests to confirm that the feature works correctly.

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Administrative account features

• Access the executions page to view pods, node details, and deployment logs for an execution.
  • Stop a test execution.
• Access the infrastructure page to view a list of currently active compute and platform nodes.
  • Verify that the number of compute and platform nodes on the infrastructure page matches the intended solution design.
• Verify that user activity reports are set up.
• Set Configuration records that match your organization’s needs. For example:
  • Send a license usage report to <usage@dominodatalab.com>.
  • Configure the maximum number of simultaneous executions per user.
• Confirm that customer_name and deployment_name are set for this deployment, or that you’ve intentionally left them unset.
• Access the workspaces page as an administrator.
• Access the control center and verify that the metrics display as expected.
• Verify that users and organizations receive in-app system notifications.
• Verify that the following events trigger an email notification:
  • Run completion.
  • Username @-mentions in comments.
  • User added as a project collaborator.

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User account features

• Create a new user account or sign in with single sign on (SSO) to your Domino instance.
• Access your Domino instance from a user account and verify that pages load correctly.
• Verify that you can access the following as a user:
  • Project portfolio.
  • Assets portfolio.

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Command Line Interface (CLI)

• Install the Domino CLI.
• Sync a project from the Domino CLI.
• Execute a batch run from the Domino CLI, and verify that results sync with your local machine.

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Compute Environment

• Create a new compute environment and verify that it builds successfully and pushes the associated image to Domino’s Docker registry.
• Add a new package and build a new compute environment.
• Add pre-run, post-run, pre-setup, and post-setup scripts and verify that they execute when you perform a run.
• Start a session in each of the following and execute code:
  • RStudio.
  • Jupyter.
  • Jupyterlab.
  • Visual Studio Code.

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Datasets

• Upload files to create Datasets and snapshots.
• Verify that shared Datasets and snapshots are mounted in a project.

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Data Sources

Connect to Data Sources that your organization uses.

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External Data Volumes

• Mount an external data volume.
• View external data volumes from the data page.
• Access external data volumes.
• Unmount an external data volume.

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Git-based Projects

• Create a Git-based project.
• Switch branches in the workspace via file changes workspace UI option.
• Resolve merge conflicts manually in Domino and push code to a remote repository.

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Logs

View the following:

• Workspace logs.
• Execution logs.
• Domino endpoint logs.
• Setup logs for workspaces and runs.
• User output logs for workspaces and runs.

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Domino endpoints

• Publish a Domino endpoint.
• Send test calls to the Domino endpoint.
• Use workspace checkpoints to open a previously published Domino endpoint version in a workspace.

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Projects

• Create a new project.
• Upload files to a project from a project’s Files Tab.
  • View the files page and verify that files render.
• Revert a project’s files to a previous commit.
• Verify that new files can sync.
• Add a Git repository to the project.
• Commit, push, and sync with a Git repository.
• Edit the volume size and launch new workspaces with the updated volume.
• Verify that results from the following actions sync back to Domino:
  • Batch run Python code to train a model.
  • Batch run R code to train a model.

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Supported clusters

The following items require that you first create the respective workspace and cluster compute environments. Attach the following to a workspace or job:

• Ray cluster.
• Spark cluster.
• Dask cluster.

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Web applications

• Start a Python Flask app and publish it from Domino.
  • Verify that Domino creates a shareable link to the app.
• Start a R Shiny app and publish it from Domino.
  • Verify that Domino creates a shareable link to the app.

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Workspaces

• Resume a workspace.
• Verify that environment variables are visible and available in workspaces.
• Start a Jupyter workspace and execute Python code.
  • Verify that results sync back to Domino.
• View the following from the workspace settings page:
  • Logs.
  • Details.
  • Resources usage.
• Start a workspace in a Domino File System project, sync a new file, and stop the workspace. Verify that you can perform the following:
  • View the history of the workspace and the file state.
  • Open a new workspace with a new branch from a previous commit.
    • In the files section of the project, view the branch name you created in the previous test.