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Contact the Anaconda implementation team before you begin for assistance upgrading your version of Data Science & AI Workbench. It is intended for you to follow along with these instructions as an Anaconda Implementation team member guides you through the upgrade process. They will provide you with a Helm Chart archive that contains all the necessary components needed for upgrading.
  • It is important to stop all sessions prior to upgrading. If you do not, sessions that are terminated as part of the upgrade process must be restarted manually post upgrade.
  • Sessions can be stopped programmatically using ae5-tools by running the following command in a terminal that has access your Workbench cluster over the network: 
    ae5 session list --columns=id --no-header | xargs -n1 ae5 session stop --yes

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Prerequisites

  • You must have access to the Administrative Server.
  • You must verify the Service Account used for the upgrade has the correct permissions.
  • Air-gapped servers must have the Docker images added to their Docker image repository.

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Upgrading

Upgrade your BYOK8s cluster by performing the following steps:
  1. Log in to the service account on the Administrative Server running your Workbench software.
  2. Unpack the Helm Charts provided by Anaconda onto the Administrative Server: 
    # Replace <HELM_CHARTS> with the Helm Charts you received from Anaconda
tar xvzf <HELM_CHARTS>
  3. Save your current configurations with the extract_config.sh script delivered with your Helm Chart by running the following command: 
    # Replace <NAMESPACE> with the namespace Workbench is installed in
NAMESPACE=<NAMESPACE> ./extract_config.sh
    The extract_config.sh script creates a file called helm_values.yaml and saves it in the directory where the script was run.
  4. Verify the information captured in helm_values.yaml file is correct and contains all of your current cluster configuration settings.
  5. Begin the upgrade by running the following command: 
    helm upgrade --values ./helm_values.yaml anaconda-enterprise ./Anaconda-Enterprise/
    If the upgrade is successful, your output will look like this: 
    Release "anaconda-enterprise" has been upgraded. Happy Helming!
NAME: anaconda-enterprise
LAST DEPLOYED: Wed Dec  7 21:52:34 2022
NAMESPACE: <YOUR_NAMESPACE>
STATUS: deployed
REVISION: 10
TEST SUITE: None
    The duration of the upgrade depends on both the cluster node count and the speed of the new docker images loading into each node.

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Verifying your upgrade

  1. Verify all pods are running by running the following command: 
    sudo kubectl get pods
  2. Open a web browser and navigate to your Authentication Center. 
    # Replace <FQDN> with the fully qualified domain name of your Workbench server
https://<FQDN>/auth/admin
  3. Select Users from the left-hand navigation, then click View all users and verify your users’ data is present.
  4. Open a new tab in your web browser and navigate to your Workbench URL. Log in using the same credentials you used for your previous installation.
  5. Review the Projects list to verify that all project data has been restored.
  6. Verify your deployments have returned to a started state.
If you are upgrading from Workbench version 5.6.2 or earlier and have RStudio installed, you must reinstall RStudio. This is due to the upgrade of the Workbench base image from UBI8 to UBI9 in version 5.7. UBI9 requires a different binary for RStudio.