Chapter 7. Resolved issues

For a complete list of updates, see the RHBA-2024:4069 advisory.

RHOAIENG-7312 - Model serving fails during query with token authentication in KServe

Previously, if you enabled both the ModelMesh and KServe components in your DataScienceCluster object and added Authorino as an authorization provider, a race condition could occur that resulted in the odh-model-controller pods being rolled out in a state that is appropriate for ModelMesh, but not for KServe and Authorino. In this situation, if you made an inference request to a running model that was deployed using KServe, you saw a 404 - Not Found error. In addition, the logs for the odh-model-controller deployment object showed a Reconciler error message. This issue is now resolved.

RHOAIENG-7079 (previously documented as RHOAIENG-6317) - Pipeline task status and logs sometimes not shown in OpenShift AI dashboard

Previously, when running pipelines by using Elyra, the OpenShift AI dashboard might not show the pipeline task status and logs, even when the related pods had not been pruned and the information was still available in the OpenShift Console. This issue is now resolved.

RHOAIENG-7070 (previously documented as RHOAIENG-6709) - Jupyter notebook creation might fail when different environment variables specified

Previously, if you started and then stopped a Jupyter notebook, and edited its environment variables in an OpenShift AI workbench, the notebook failed to restart. This issue is now resolved.

RHOAIENG-6853 - Cannot set pod toleration in Elyra pipeline pods

Previously, if you set a pod toleration for an Elyra pipeline pod, the toleration did not take effect. This issue is now resolved.

RHOAIENG-6505 - Disconnected environments: Extra image needed for RayCluster TLS certificate creation

Previously, if you tried to implement mutual Transport Layer Security (mTLS) for distributed workloads in a disconnected environment, you had to add an additional default image (quay.io/project-codeflare/ray:latest-py39-cu118) to your mirror registry for TLS certificate creation for Ray Clusters. This issue is now resolved.

RHOAIENG-5314 - Data science pipeline server fails to deploy in fresh cluster due to network policies

Previously, if you created a data science pipeline server on a fresh cluster, the user interface remained in a loading state and the pipeline server did not start. This issue is now resolved.

RHOAIENG-4252 - Data science pipeline server deletion process fails to remove ScheduledWorkFlow resource

Previously, the pipeline server deletion process did not remove the ScheduledWorkFlow resource. As a result, new DataSciencePipelinesApplications (DSPAs) did not recognize the redundant ScheduledWorkFlow resource. This issue is now resolved

RHOAIENG-3411 (previously documented as RHOAIENG-3378) - Internal Image Registry is an undeclared hard dependency for Jupyter notebooks spawn process

Previously, before you could start OpenShift AI notebooks and workbenches, you must have already enabled the internal, integrated container image registry in OpenShift Container Platform. Attempts to start notebooks or workbenches without first enabling the image registry failed with an "InvalidImageName" error. You can now create and use workbenches in OpenShift AI without enabling the internal OpenShift Container Platform image registry. If you update a cluster to enable or disable the internal image registry, you must recreate existing workbenches for the registry changes to take effect.

RHOAIENG-2541 - KServe controller pod experiences OOM because of too many secrets in the cluster

Previously, if your OpenShift cluster had a large number of secrets, the KServe controller pod could continually crash due to an out-of-memory (OOM) error. This issue is now resolved.

RHOAIENG-1452 - The Red Hat OpenShift AI Add-on gets stuck

Previously, the Red Hat OpenShift AI Add-on uninstall did not delete OpenShift AI components when the install was triggered via OCM APIs. This issue is now resolved.

RHOAIENG-307 - Removing the DataScienceCluster deletes all OpenShift Serverless CRs

Previously, if you deleted the DataScienceCluster custom resource (CR), all OpenShift Serverless CRs (including knative-serving, deployments, gateways, and pods) were also deleted. This issue is now resolved.