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Chapter 12. Managing notebook servers

12.1. Accessing notebook servers owned by other users

Administrators can access notebook servers that are owned by other users to correct configuration errors or help a data scientist troubleshoot problems with their environment.

Prerequisites

  • You are part of the OpenShift Dedicated administrator group. See Adding administrative users for OpenShift Dedicated for more information.
  • You have launched the Jupyter application. See Launching Jupyter and starting a notebook server.
  • The notebook server that you want to access is running.

Procedure

  1. On the page that opens when you launch Jupyter, click the Administration tab.

  2. On the Administration page, perform the following actions:

    1. In the Users section, locate the user that the notebook server belongs to.
    2. Click View server beside the relevant user.
    3. On the Notebook server control panel page, click Access notebook server.

Verification

  • The user’s notebook server opens in JupyterLab.

12.2. Stopping idle notebooks

You can reduce resource usage in your OpenShift Data Science deployment by stopping notebook servers that have been idle (without logged in users) for a period of time. This is useful when resource demand in the cluster is high. By default, idle notebooks are not stopped after a specific time limit.

Note

If you have configured your cluster settings to disconnect all users from a cluster after a specified time limit, then this setting takes precedence over the idle notebook time limit. Users are logged out of the cluster when their session duration reaches the cluster-wide time limit.

Prerequisites

  • You have logged in to Red Hat OpenShift Data Science.
  • You are part of the OpenShift Data Science administrator group in OpenShift Container Platform.

Procedure

  1. From the OpenShift Data Science dashboard, click Settings Cluster settings.
  2. Under Stop idle notebooks, select Stop idle notebooks after.
  3. Enter a time limit, in hours and minutes, for when idle notebooks are stopped.
  4. Click Save changes.

Verification

  • The notebook-controller-culler-config ConfigMap, located in the redhat-ods-applications project on the Workloads ConfigMaps page, contains the following culling configuration settings:

    • ENABLE_CULLING: Specifies if the culling feature is enabled or disabled (this is false by default).
    • IDLENESS_CHECK_PERIOD: The polling frequency to check for a notebook’s last known activity (in minutes).
    • CULL_IDLE_TIME: The maximum allotted time to scale an inactive notebook to zero (in minutes).
  • Idle notebooks stop at the time limit that you set.

12.3. Configuring a custom notebook image

In addition to notebook images provided and supported by Red Hat and independent software vendors (ISVs), you can configure custom notebook images that cater to your project’s specific requirements.

Red Hat supports you in adding custom notebook images to your deployment of OpenShift Data Science and ensuring that they are available for selection when creating a notebook server. However, Red Hat does not support the contents of your custom notebook image. That is, if your custom notebook image is available for selection during notebook server creation, but does not create a usable notebook server, Red Hat does not provide support to fix your custom notebook image.

Prerequisites

  • You have logged in to Red Hat OpenShift Data Science.
  • You are assigned the cluster-admin role in OpenShift Container Platform.
  • Your custom notebook image exists in an image registry and is accessible.

Procedure

  1. From the OpenShift Data Science dashboard, click Settings Notebook images.

    The Notebook image settings page appears. Previously imported notebook images are displayed. To enable or disable a previously imported notebook image, on the row containing the relevant notebook image, click the toggle in the Enabled column.

  2. Click Import new image. Alternatively, if no previously imported images were found, click Import image.

    The Import Notebook images dialog appears.

  3. In the Repository field, enter the URL of the repository containing the notebook image.
  4. In the Name field, enter an appropriate name for the notebook image.
  5. In the Description field, enter an appropriate description for the notebook image.

  6. Optional: Add software to the notebook image. After the import has completed, the software is added to the notebook image’s meta-data and displayed on the Jupyter server creation page.

    1. Click the Software tab.
    2. Click the Add software button.
    3. Click Edit ( The Edit icon ).
    4. Enter the Software name.
    5. Enter the software Version.
    6. Click Confirm ( The Confirm icon ) to confirm your entry.
    7. To add additional software, click Add software, complete the relevant fields, and confirm your entry.

  7. Optional: Add packages to the notebook images. After the import has completed, the packages are added to the notebook image’s meta-data and displayed on the Jupyter server creation page.

    1. Click the Packages tab.
    2. Click the Add package button.
    3. Click Edit ( The Edit icon ).
    4. Enter the Package name.
    5. Enter the package Version.
    6. Click Confirm ( The Confirm icon ) to confirm your entry.
    7. To add an additional package, click Add package, complete the relevant fields, and confirm your entry.
  8. Click Import.

Verification

  • The notebook image that you imported is displayed in the table on the Notebook image settings page.
  • Your custom notebook image is available for selection on the Start a notebook server page in Jupyter.

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