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Once you have successfully completed installation, there are some additional steps to take before beginning to use Data Science & AI Workbench.

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Final configuration steps

  1. (Gravity only) To add worker nodes to the cluster, follow the instructions in our adding and removing nodes topic.
  2. Wait for the application to fully stabilize. Workbench can take up to 30 minutes to fully finish loading, depending upon the performance of the cluster network and attached disks. You may be able to log in to the main UI immediately, but sessions and deployments will not be ready to start.
  3. Confirm that the cluster has loaded by running the following command from the master node: 
    watch kubectl get pods
    Wait for every pod to indicate a status of either Running or Completed. The app-images pods will be the last to stabilize. You can exit the watch command at any time with ctrl-C.

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Testing your installation

Once the application has fully loaded, you can do the following to verify that your installation succeeded.
  1. Access the Workbench console by entering the URL of your Workbench server in a web browser: https://anaconda.example.com, replacing anaconda.example.com with the fully-qualified domain name of the host server.
  2. Log in using the default username and password anaconda-enterprise / anaconda-enterprise.
  3. Update the passwords for your anaconda-enterprise and admin users. See Configuring user access for information and steps for updating your password.
    Do not alter the anaconda-enterprise account username; it is used for certain cluster administration functions.
If you do not update your passwords, anyone with the default credentials will be able to access your admin console. This poses a security risk, so it is important to change these passwords immediately. You can verify a successful installation by doing any or all of the following:
Some of the sample projects can only be deployed after mirroring the package repository. To test your installation without doing this first, you can deploy the “Hello Anaconda Enterprise” sample project.
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