Known issues

Initial project creation, edit, or deployment fails

On a new installation/upgrade of Anaconda Enterprise, or a newly installed node that has not yet created, deployed, or edited a project, the project action can fail the first time an action is performed and will appear as a timeout or stuck deployment. This occurs because the initial project create/deploy/edit action pulls an editor or deployment image to the node.

Workaround

Wait for the initial project create/deploy/edit action to complete without deleting the project. This can take up to 5 minutes, depending on your disk and network transfer speed. Once the image is pulled to a particular cluster node, subsequent project create/deploy/edit actions on that node will occur without the initial delay that was experienced.

You can confirm that the image pull is occurring on a particular editor session or deployment by examining the associated pod as an administrator on any cluster node:

$ sudo gravity enter
# kubectl describe pods anaconda-app-XXXXX-XXXXX-XXXXX
Events:
  FirstSeen LastSeen        Count   From                    SubObjectPath                                                   Type            Reason                  Message
  --------- --------        -----   ----                    -------------                                                   --------        ------                  -------
  3m                3m              1       default-scheduler                                                                       Normal          Scheduled               Successfully assigned anaconda-space-beb77fc211124be1babed34dd888e26f-1605686975l74vs to 172.31.28.22
  3m                3m              1       kubelet, 172.31.28.22                                                                   Normal          SuccessfulMountVolume   MountVolume.SetUp succeeded for volume "no-api-access-please"
  3m                3m              1       kubelet, 172.31.28.22                                                                   Normal          SuccessfulMountVolume   MountVolume.SetUp succeeded for volume "project-working-copy"
  3m                3m              1       kubelet, 172.31.28.22                                                                   Normal          SuccessfulMountVolume   MountVolume.SetUp succeeded for volume "anaconda-secrets"
  3m                3m              1       kubelet, 172.31.28.22                                                                   Normal          SuccessfulMountVolume   MountVolume.SetUp succeeded for volume "anaconda-proxy-secrets"
  3m                3m              1       kubelet, 172.31.28.22                                                                   Normal          SuccessfulMountVolume   MountVolume.SetUp succeeded for volume "anaconda-config-files"
  3m                3m              1       kubelet, 172.31.28.22                                                                   Normal          SuccessfulMountVolume   MountVolume.SetUp succeeded for volume "default-token-fg320"
  3m                3m              1       kubelet, 172.31.28.22   spec.containers{tool-proxy-7aabd630a9a74c7385fa828112ebce77}    Normal          Pulling                 pulling image "apiserver:5000/ap-app-proxy:5.1.0rc9"

where anaconda-app-XXXXX-XXXXX-XXXXX is the name of the pod. You should see a message related to pulling image in the last line of the list of events that will complete once the image is successfully pulled to the cluster node.

Affected Versions

5.0.5, 5.0.6, 5.1.0

Jupyter Kernel not showing up JupyterLab launcher

When launching a project that based on the R or Spark template, or a project that has custom Jupyter kernels it might take a while to see the Jupyter kernels appear in the JupyterLab launcher. If they dont show up after a couple of minutes you need to refresh this view.

Workaround

Go to the “Project” tab in the left sidebar. Open the environments section and click on the checkmark icon. The Spark and R related kernels should show up now.

Affected Versions

5.1.0

Updating a package from from the anaconda metapackage

When updating a package dependency of a project, if that dependency is part of the Anaconda metapackage the package will be installed once but a subsequent anaconda-project call will uninstall the upgraded package.

Workaround

When updating a package dependency remove the anaconda metapackage from the list of depedencies at the same time add the new version of the dependency that you want to update.

Affected Versions

5.1.0

IE 11 compatibility issue when using Bokeh in projects (including sample projects)

Bokeh plots and applications have had a number of issues with Internet Explorer 11, which typically result in the user seeing a blank screen.

Workaround

Upgrade to the latest version of Bokeh available. On Anaconda 4.4 the latest is 0.12.7. On Anaconda 5.0 the latest version of Bokeh is 0.12.13. If you are still having issues, consult the Bokeh team or support.

Affected Versions

5.1.0

IE 11 compatibility issue when downloading custom Anaconda installers

Unable to download a custom Anaconda installer from the browser when using Internet Explorer 11 on Windows 7. Attempting to download a custom installer with this setup will result in an error that “This page can’t be displayed”.

Workaround

Custom installers can be downloaded by refreshing the page with the error message, clicking the “Fix Connection Error” button, or using a different browser.

Affected Versions

5.1.0