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Chapter 7. Resolved issues
The following notable issues are resolved in Red Hat OpenShift AI 2.15. Security updates, bug fixes, and enhancements for Red Hat OpenShift AI 2.15 are released as asynchronous errata. All OpenShift AI errata advisories are published on the Red Hat Customer Portal.
7.1. Issues resolved in Red Hat OpenShift AI 2.15
RHOAIENG-14571 - Data Science Pipelines API Server unreachable in managed IBM Cloud OpenShift OpenShift AI installation
Previously, when configuring a data science pipeline server, communication errors that prevented successful interaction with the pipeline server occurred. This issue is now resolved.
RHOAIENG-14195 - Ray cluster creation fails when deprecated head_memory parameter is used
Previously, if you included the deprecated head_memory parameter in your Ray cluster configuration, the Ray cluster creation failed. This issue is now resolved.
RHOAIENG-11895 - Unable to clone a GitHub repo in JupyterLab when configuring a custom CA bundle using |-
Previously, if you configured a custom Certificate Authority (CA) bundle in the DSCInitialization (DSCI) object using |-, cloning a repo from JupyterLab failed. This issue is now resolved.
RHOAIENG-1132 (previously documented as RHODS-6383) - An ImagePullBackOff error message is not displayed when required during the workbench creation process
Previously, pods experienced issues pulling container images from the container registry. When an error occurred, the relevant pod entered into an ImagePullBackOff state. During the workbench creation process, if an ImagePullBackOff error occurred, an appropriate message was not displayed. This issue is now resolved.
RHOAIENG-13327 - Importer component (dsl.importer) prevents pipelines from running
Pipelines could not run when using the data science pipelines importer component, dsl.importer. This issue is now resolved.
RHOAIENG-14652 - kfp-client unable to connect to the pipeline server on OCP 4.16 and later
In OpenShift 4.16 and later FIPS clusters, data science pipelines were accessible through the OpenShift AI Dashboard. However, connections to the pipelines API server from the KFP SDK failed due to a TLS handshake error. This issue is now resolved.
