Known Issues and Limitations

You might run into some known issues while using Cloudera Machine Learning on Private Cloud.

Do not use backtick characters in environment variable names

Avoid using backtick characters ( ` ) in environment variable names, as this will cause sessions to fail with exit code 2.

Model Registry is not supported on R models

Model Registry is not supported on R models.

Model Registry model name cannot exceed 19 characters

The Model Registry model name cannot exceed 19 characters.

After upgrading a workspace, the pod evaluator is in CrashLoopBackOff state

This typically happens after a workspace upgrade. The solution is to upgrade the workspace as soon as the Control Plane is upgraded.

Migration from CDSW fails if Enable Model Metrics is not selected

CDSW to CML migration fails if you do not select the Enable Model Metrics option.

Workaround: In Cloudera Machine Learning Workspaces, Provision Workspace (CDSW Migration), select the Enable Model Metrics option:

DSE-24690 CDSW to CML migration fails with the Cloudera default docker repository

During CDP Private Cloud installation, you are prompted to configure the Docker repository that Cloudera uses to deliver CDP Private Cloud Services. Choosing Use Cloudera's default Docker Repository can cause the Cloudera Data Science Workbench (CDSW) to CML migration to fail.

Workaround: During installation, in Configure Docker Repository, choose either one of the following options:
  • Use an embedded Docker Repository
  • Use a custom Docker Repository

The mlflow.log_model registered model files might not be available on NFS Server

When using mlflow.log_model, registered model files might not be available on the NFS server due to NFS server settings or network connections. This could cause the model to remain in the registering status.

  • Re-register the model. It will register as an additional version, but it should correct the problem.
  • Add the ARTIFACET_SYNC_PERIOD environment variable to ds-vfs Kubernetes deployment and set it to an integer value. This will set the model registry retry operation to twice the number of seconds specified by the artifact sync period integer value. If the ARTIFACET_SYNC_PERIOD is set to 30 seconds then model registry will retry for 60 seconds. The default value is 10 and model registry retries for 20 seconds. For example: -name: ARTIFACT_SYNC_PERIOD value: “30”.

DSE-23329: Spark API fails when reading or writing to Ozone filesystem

CML with Spark as a runtime addon does not work with the Ozone file system.

DSE-33636: Workloads unable to start up after changing default hadoopCLI addon

Changing the default Hadoop CLI Runtime Addon causes jobs, models, and application workloads to be unable to start up.

  1. Open affected workload settings.
  2. Update the workload (this updates the Hadoop CLI Addon associated with the workload to the default one.)
  3. For Jobs: update.
  4. For Applications: update and restart.
  5. For Models: deploy a new build.
Please see Machine Learning Site administration>Disable Addons for related tasks.

DSE-20923: User search requires lower case

When searching for a user name in Site Administration > Users, you must enter only lower-case letters for the name you are searching for. Lower-case letters will match upper-case letters in the target name.

DSE-19036: Model and experiment building fails after ECS upgrade

After ECS Control Plane upgrade, your ML workspace may fail to perform Model and Experiment building with a message like: Cannot connect to the Docker daemon at unix:///var/run/docker.sock. Is the docker daemon running?

To resolve this problem, perform these steps:

  1. Access Cloudera Manager
  2. Navigate to the Embedded Cluster ECS Web UI: Clusters > Your Embedded Cluster > ECS > Web UI > ECS Web UI
  3. Select the namespace of your ML workspace on the top left dropdown.
  4. In Workloads > Deployments, locate s2i-builder in the list.
  5. In the Action menu for s2i-builder, select Restart.

DSE-13117: Container Image Registries assuming mutual TLS for authentication are not supported

If Private Cloud images are hosted in an image registry assuming mutual TLS for authentication, this will cause Model deployments and Experiments to fail. Mutual TLS registries are not supported.

DSE-12541: Self Signed Certificates for Container Registry cause Models and Experiments to fail

If you are using self-signed or Private CA signed certificates for Container image registry authentication, model deployements and experiments will fail with an error similar to: Error initializing source docker://<registryIP>:5000/alpine:latest: error pinging docker registry <registryIP>:5000: Get https://<registryIP>:5000/v2/: x509: certificate signed by unknown authority

As a workaround, create a ConfigMap in the namespace where the CML workspace is installed.

  1. Create a ConfigMap as shown in this example. Here, <namespace> indicates the workspace where the CML workspace is installed.

    kind: ConfigMap
    apiVersion: v1
      name: <external-registry-name>
      Namespace: <namespace> 
      registry.crt: |
        -----BEGIN CERTIFICATE-----
        < certificate content goes here >
        -----END CERTIFICATE-----
        -----BEGIN CERTIFICATE-----
        < certificate content goes here >
        -----END CERTIFICATE-----
  2. Mount the ConfigMap to the s2i-builder deployment as shown here. Add the following mountPath in the volumeMounts section for the s2i-builder pod:

    - mountPath: /etc/docker/certs.d/<registry>[:portnum]
      name: external-registry

    Under the volumes section, add the ConfigMap reference:

    - configMap:
         defaultMode: 420
         name: <external-registry-name>
      name: external-registry
  3. Run the following command and check the output. Note in particular the mountPath and configMap specifications at the end.

    # kubectl get deployment s2i-builder -n <namespace> -o yaml
    apiVersion: extensions/v1beta1
    kind: Deployment
      name: s2i-builder
      namespace: <namespace/workspacename>
        - name: s2i-builder
              - mountPath:/etc/docker/certs.d/<registry>[:portnum]
                name: external-registry
      - configMap:
          defaultMode: 420
          name: <external-registry-name>
        name: external-registry

DSE-12367: s2i-queue pod goes into CrashLoop Failure causing ML workspace installation to fail

CML workspace install can fail because the s2i-queue pod may be stuck in a CrashLoop Failure. The error in the logs might look similar to: Failed to create thread: Resource temporarily unavailable (11) /usr/lib/rabbitmq/bin/rabbitmq-server: line 182: 45 Aborted (core dumped) start_rabbitmq_server "$@" Only root or rabbitmq can run rabbitmq-server

To fix this, apply the following workaround: # kubectl set env statefulset/s2i-queue RABBITMQ_IO_THREAD_POOL_SIZE="50" -n <namespace>

DSE-12329: Email invitation feature

The feature to invite new users by email does not work in Public or Private cloud, but it still appears in the UI.

DSE-12289: Airgap support: Proxies are not supported in CML Private Cloud 1.0

Use of a proxy server, for example for external internet connectivity for an airgap cluster, is not supported. Transparent proxies, however, should work normally.

DSE-12238: Create Project request takes longer than timeout

If a Create Project request takes longer than a certain timeout, a second request might be submitted. If this happens, multiple projects with similar names might be created.

As a workaround, create an empty project, create a session inside the project, then git clone your project inside a workbench terminal. Additionally, you can upload a zip file or a folder using the file preview table.

If multiple forks are created, delete the extra ones.

DSE-12090: User displays as unknown in Event History

In the Event History on the workspace Events tab, a user may display as unknown if they are authenticated by LDAP.

Fix: The user needs to be assigned the IamViewer role to view these details.

DSE-11979: Certificate failure when pulling images from the S2I container registry

During Model or Experiment deployment, a certificate failure similar Failed to pull image x509: certificate signed by unknown authority can occur. This is due to a Red Hat issue with OpenShift Container Platform 4.3.x where the image registry cluster operator configuration must be set to Managed.

To set the configuration, first apply a patch using this command: # oc patch cluster --patch '{"spec":{"managementState":"Managed"}}'

Next, run the following command: # oc get config cluster -o yaml

The managementState is now set to Managed.

DSE-11870: Hung File, Stale File, and Fork issues with NFS

Hung File Operations: Certain file operations, such as stat(2) or stat(1) might stop responding, and if the file operation was performed through the CML web UI, the web operation might timeout. This indicates an NFS server that is not reachable for some reason. The error might manifest itself on the web UI when you try to open an ML project as an HTTP error, code 500. Check the logs for error messages similar to the following:

 2020-07-13 22:42:23.914 1 ERROR AppServer.Lib.Utils Finish grpc, failed data =
        DEADLINE_EXCEEDED: Deadline Exceeded","Error: 4 DEADLINE_EXCEEDED: Deadline Exceeded\n at
        Object.exports.createStatusError (/home/cdswint/services
        /web/node_modules/grpc/src/common.js:91:15)\n at Object.onReceiveStatus
        (/home/cdswint/services/web/node_modules/grpc/src/client_interceptors.js:1209:28)\n at
        InterceptingListener._callNext (/home/cdswint/services/web/
        node_modules/grpc/src/client_interceptors.js:568:42)\n at
        (/home/cdswint/services/web/node_modules/grpc/src/client_interceptors.js:618:8)\n at
        callback (/home/cdswint/services/web/n

Solution: Check your NFS server and make sure it is running. You will need to restart the NFS clients in your ML workspace’s namespace. These are the “ds-vfs” and “s2i-client” pods. Simply delete the Kubernetes pods whose names start with “ds-vfs” and “s2i-client”.

Stale File Handles: When opening a project from the ML web UI, an error message like “NFS: Stale file handle” shows up on the UI.

Solution: This is indicative of an NFS server and a client being out of sync, probably caused by a server restart along with file system content change on the server that the client is not aware of. You should restart NFS client pods in your ML workspace’s namespace. The are the “ds-vfs”, “s2i-client”, and any user sessions that are affected by the “Stale file handle” error.

Project Fork Creating Multiple Copies: When creating a new project from an existing project using the “Fork” feature, you might see the operation seemingly fail on the UI, but it still ends up creating multiple copies of the source project.

Solution: This issue happens when forking a project takes longer than the idle connection timeout set on the external load balancer, as well as in HA Proxy policy settings on OpenShift. Increase the idle connection timeout to at least 5 minutes. Depending on the performance of the NFS server, a higher timeout may be necessary.

DSE-11837: Timeout limitation for Project API

If you create a project in the UI using git clone, you may get the error message Whoops, there was an unexpected error. If you create a project using the API, a timeout may occur.

Prerequisites for CML in Private Cloud:

  • Set any external load balancer server timeout to 5 min.

For a TLS Enabled Workspace:

  • Set the annotation on each route in a deployed CML workspace namespace:
    oc annotate route --all=true --overwrite=true -n

For non-TLS Enabled Workspaces, this setting is made automatically.

Workaround: Even though an error message displays, project creation still occurs. Check the Projects page after a few minutes; project creation should be complete.

DSE-9549: TLS enabled workspaces require manual configuration

To provision a TLS-enabled workspace, the customer needs to perform several manual steps. This procedure is described in Deploy an ML Workspace with Support for TLS.

OPSAPS-58019: CML workspace installation failure due to includedir in krb5.conf file

If the /etc/krb5.conf on the Cloudera Manager host contains include or includedir directives, Kerberos-related failures may occur.

As a workaround, comment out the include and includedir lines in /etc/krb5.conf on the Cloudera Manager host. If configuration in those files and directories are needed, add them directly to /etc/krb5.conf.

DSE-21768: Spark3 runtime addons are not supported with Python 3.8 Runtimes

If the /etc/krb5.conf on the Cloudera Manager host contains include or includedir directives, Kerberos-related failures may occur.

Spark3 runtime addons are currently not supported with Python 3.8 Runtimes.