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Chapter 2. New features and enhancements
This section describes new features and enhancements in Red Hat OpenShift AI.
2.1. New features Copiar enlaceEnlace copiado en el portapapeles!
- Toggle added for stopping and starting KServe serverless models
With this update, you can stop and start deployed models to better manage resources and costs. When a model is not in use, you can stop it to release its dedicated resources, including GPUs. When you need the model again, you can restart it.
This feature is available on the Model deployments page for models deployed on the single-model serving platform.
2.2. Enhancements Copiar enlaceEnlace copiado en el portapapeles!
- Support added for enabling and disabling caching on Elyra nodes
- You can now specify caching settings for individual nodes within Elyra pipelines. With this update, you can manage the caching option for each pipeline node in the Node Properties panel dropdown and enable or disable caching settings per node in Elyra pipelines.
- Model registry database configuration update
From OpenShift AI version 2.23, if the external database associated with your model registry instance is configured to enforce Transport Layer Security (TLS), then you must add a Certificate Authority (CA) certificate for the database.
Existing model registries will fail if the associated database enforces TLS and you did not add a CA certificate. Affected model registries will appear with an
Unavailable
status on the Model registry settings page, and you might seeRetrying connection to MySQL
errors in the pod logs for the registry.You can add a certificate by selecting the Add CA certificate to secure database connection option when you create or edit your model registry. For more information about creating and editing a model registry instance, see Managing model registries.
- Custom namespaces for workbenches
-
You can now configure workbenches to run in a user-defined namespace. This is useful for environments with specific namespace policies or naming procedures. When you enable the workbenches component, set the
spec.workbenches.workbenchNamespace
field in theDataScienceCluster
custom resource to specify the custom namespace. You cannot migrate existing workbenches to the new custom namespace.
- Updated workbench images
- Python 3.12 workbench images are now available in OpenShift AI for JupyterLab and code-server IDEs. This update addresses issues related to multithreading and memory management and includes performance enhancements and general improvements.