Data Science & AI Workbench can be installed on a wide variety of CNCF-compliant Kubernetes cluster. Installation is performed using the industry standard Helm package manager. Successful deployment requires the expertise of your in-house Kubernetes administrators to validate our requirements and provision the necessary compute, storage, and networking resources.

After you have verified that your environment is prepared for installation by completing the pre-installation checklist, you are ready to install the cluster!

Perform the following actions from your established administration server.

  1. Installation is largely performed in the custom namespace. Modify the default kubectl context to point to the new namespace by running the following command:

    # Replace <NAMESPACE> with the namespace that you reserved for Workbench
kubectl config set-context --current --namespace=<NAMESPACE>

    The remainder of these instructions assume this change has been made.

  2. Open and unpack the Helm chart archive provided by Anaconda, and cd into the root directory of this archive.

    The archive root directory contains the following items of importance:

    • The Anaconda-Enterprise/ directory. This contains your helm chart.
    • The values.yaml override file. Edit this file to include custom configurations for the application.
    • A version of these instructions labeled as INSTALL.{md,pdf}.

  3. If you need a pull secret to access the Docker registry, create it now, then verify the presence of the pull secret by running the following command:

    # Replace <PULL_SECRET_NAME> with the name for your pull secret
kubectl describe secret <PULL_SECRET_NAME>

  4. Using your preferred text editor, open the values.yaml override file. Add or modify necessary values to this file. At minimum, you must provide the following:

  5. Start your installation by running the following command:

    helm install --values ./values.yaml anaconda-enterprise ./Anaconda-Enterprise/

    The current version of Workbench requires the release name anaconda-enterprise. Do not change this value.

  6. Monitor the progress of your installation by running the following command:

    watch kubectl get pods

  7. Wait for all of the pods to get to the Running or Completed state.

    Installation can take several minutes depending on the performance characteristics of your system. If a particular pod is behaving in an unexpected manner, you can investigate the cause using commands such as:

    # Replace <POD_NAME> with the name of the pod
kubectl logs <POD_NAME>
kubectl describe pod <POD_NAME>

  8. If you chose to install the Anaconda-supplied ingress, you must now need to determine its assigned IP address, and create your DNS records for the cluster. To determine this address, run the command:

    kubectl get svc anaconda-enterprise-nginx.ingress

    The IP address is provided in the External IP column. Create your DNS records for your FQDN and for its wildcard. For example, anaconda.example.com and *.anaconda.example.com.

    Once these DNS changes have propagated, you can proceed to the next step.

  9. Open a web browser and navigate to your instance of Workbench.

    Your browser may initially refuse to connect due to the use of our generated, self-signed SSL certificates. You should temporarily permit your browser to proceed anyway. You will also have to do the same every time you start a new session or deployment, so it is best to complete the next step as soon as possible.

  10. Update your SSL certificates.

    If you are installing the Anaconda-supplied ingress, you can expect it to enter a CrashLoopBackoff state until the SSL certificate generation task has completed. This is expected behavior. Once the preliminary certificates are generated, the next automatic restart of the ingress should proceed without incident.

Basic installation of Workbench is now complete! You can now perform any additional post-installation steps necessary.

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