Cloudera Docs

What's New

Major features and updates for the Cloudera AI data service.

October 31, 2025

Release notes and fixed issues for version 2.0.53-b243.

New Features / Improvements

Model Hub
  • Improved model information display by surfacing attributes like MaxTokens, Parameters, and Dimensions for Embedding Models, enabling better decision-making before importing models.
Cloudera AI Inference service
  • Added the ability for users to start and stop deployed model endpoints, providing greater control over resource management and cost optimization. This feature allows you to pause inactive endpoints to save resources while maintaining the ability to quickly restart them when needed.
  • Improved user experience by enabling customers to open model endpoints in different browser tabs, allowing for better multitasking and simultaneous monitoring of multiple endpoints.
  • Enhanced API accessibility by providing customers access to the Swagger UI for invoking AI Inference APIs, enabling interactive API testing and documentation exploration.
  • Added visibility to the underlying compute cluster through a direct link in the UI for AI Inference instances, providing seamless navigation to cluster details and infrastructure monitoring.
  • Implemented validation for root volume size when adding new nodes to AI Inference deployments, preventing configuration errors and ensuring adequate storage capacity.
  • Enhanced node group management by displaying GPU types and enabling filtering based on GPU type when searching through available nodes, improving resource selection efficiency.
  • Upgraded KServe from version 0.12 to 0.15, enhancing the underlying model serving infrastructure.
Cloudera AI Platform
  • Enhanced support for self-signed certificates in public cloud deployments, resolving installation and update pain points. For more information, see Managing Certificate Authority certificates.
  • Re-enabled cadence workflow for workbench upgrades, fixing version compatibility issues.
Cloudera AI Workbench
  • Optimized the loading speed of the Site Administration overview and the Projects pages by improving cluster-wide resource usage data collection, ensuring quick loading even in environments with 1,000+ user namespaces.
  • The Job Retry feature introduces automated recovery for failed, timed out, or skipped jobs. Administrators can now set concurrent retry limits and customize the retry behavior to enhance job resilience and eliminate the need for manual failure intervention. For more information, see Configuring Job Retry settings.

Fixed Issues

Cloudera AI Registry
  • Fixed Events & Logs rendering during the creation of new registries in the UI. (DSE-48101)
Cloudera AI Inference service
  • Resolved inconsistencies in the tooltips displayed on the Model Endpoint Details page, ensuring accurate and helpful information is shown to users. (DSE-45042)
  • The API service can now inspect the metadata of MLflow models from the Cloudera AI Registry to correctly identify the Hugging Face transformer flavor. This ensures the model is automatically routed to the correct runtime (i.e. HuggingFace runtime with vLLM backend unlike defaulting to Triton + ONNX earlier), enabling successful deployment of MLflow transformer models. (DSE-46462)
Cloudera AI Workbench
  • Removed the rigid requirement for every team to have an Administrator, allowing Team Administrators (or Site Administrators if none are designated) to manage team membership and roles. (DSE-41700)
  • You can now customize the model build process with two new options: model_root_dir allows setting a custom source directory, and build_script_path enables specifying a custom location for the build script. (DSE-45166)
  • Resolved a page layout issue that occurred after horizontal window resizing. The fix ensures the browser view restores correctly without requiring a manual refresh. (DSE-40393).
MLRuntimes
  • Fixed an issue where system messages were hidden or suppressed when a Workload (such as a Session, Job, or Application) failed to start up while using a PBJ Workbench Runtime. (DSE-46126)

Behavioral Change

MLRuntimes
  • The R kernel output mechanism has been updated to improve visibility of interactive commands. The output of R commands (for example, install.packages("sparklyr")) is now mirrored to both the Session tab and the Logs tab by default, rather than appearing solely in the Logs. This ensures immediate visibility of important messages like installation progress, compilation output, and errors. Users can revert to the previous behavior by setting the environment variable JUPYTER_KERNEL_OUTPUT_FILTER_REGEX to "DISABLED" or "^$". (DSE-35335)
  • Clearing a session now permanently removes all content from the session history, ensuring that subsequent PDF exports and email reports contain only current, relevant results and no stale data from previous runs. (DSE-12565)
Cloudera AI Inference service
  • MLFlow integration with transformer models is now complete, enabling models saved using the workbench (via MLFlow) in the Hugging Face transformer format to be successfully deployed on Cloudera AI Inference service, including both regular and finetuned models. (DSE-43840)

September 25, 2025

Release notes and fixed issues for version 2.0.52-b<TBA>.

New Features / Improvements

Cloudera AI Registry
  • You can now update the visibility of models directly from the UI.
  • You can now delete registries in a failed status directly from the UI.
  • Added the ability to use pre-downloaded artifacts when importing external models.
  • The model card for embedding models now includes MaxTokens, Parameters, and Dimensions.
  • Added support for upgrading Azure registries with UDR-enabled subnets.

  • Improved error resolution suggestions have been added to the UI for Cloudera AI Registry, empowering users to troubleshoot issues on their own.

Cloudera AI Inference service
  • Added support for new models, including NeMo Retriever’s GraphicElements, PageElements, and TableStructure, as well as PaddleOCR, Boltz-2, and GPT-OSS models.
  • The Test Model feature is now available for Speech-to-Text models.
  • You can now specify vLLM arguments when deploying Hugging Face models.
  • Improved error resolution suggestions have been added to the UI for Cloudera AI Inference service empowering users to troubleshoot issues on their own.
  • Grouped CPU/GPU nodes under the Cloudera AI Inference service Details page for a more user-friendly experience.
Cloudera AI Platform
  • You can now provision multiple CPU/GPU resource groups in the Cloudera AI Workbench. This provides enhanced control over workload scheduling and allows segregation of workloads based on the instance types.

  • Added support for EKS 1.32.

  • Added support for AKS 1.32.

Fixed Issues

Cloudera AI Inference service
  • Addressed critical CVEs in most NGC models by upgrading to the latest NIM versions. (DSE-47435)

  • Resolved an issue where code samples were not correctly rendered for riva, reranking, and retrieval models. (DSE-46413)

  • Ensured that the UI carries out proper validation of GPU, CPU, and memory during model deployment. (DSE-46250)

  • Resolved an issue where Prometheus errors were not surfaced in the Model Endpoints UI. (DSE-46077)

  • Addressed an accessibility issue with the 'Deploy external dropdown button'. (DSE-46071)

  • Resolved an issue that blocked navigation to other tabs while waiting for a response from the Model Endpoint's Test Model. (DSE-46247)

  • Resolved an issue where a scale alert box was not displayed in the UI when the model endpoint was ready and the current replica count was zero. (DSE-46301)

Cloudera AI Registry
  • Resolved an issue where the UI did not properly surface failures occurring during NVIDIA model imports from the Model Hub page. (DSE-45971)
  • Resolved an issue where the UI was not correctly auto-selecting the running registry. (DSE-46246)
  • Resolved an issue that prevented users from registering models from within a workbench. (DSE-47077)
Cloudera AI Workbench
  • Resolved an issue where proxy environment variables were being overwritten during model builds. (DSE-46070)
  • Resolved an issue where the Project Settings page displayed the project owner's ID instead of their name. (DSE-46572)
Cloudera AI Platform
  • Resolved an issue where spaces were incorrectly added to the ldap_dn during synchronization of some users, which caused those members of CML groups to be unintentionally removed. (DSE-47591)

August 22, 2025

Release notes and fixed issues for version 2.0.52-b34.

New Features / Improvements

ML Runtimes
  • Released new Spark Runtime Addons versions - 2.4.8, 3.2.3, 3.3.0, and 3.5.1.
  • Spark 3.5.1 in Cloudera AI is now certified to work with the Data Lake 7.3.1 version.
  • New HadoopCLI Runtime Addon versions 7.2.18 and 7.3.1 are now available. Versions 7.2.16 and 7.2.17 have been removed.

Fixed Issues

Cloudera AI Registry
  • Resolved an issue that blocked AI Registry creation in regions other than us-west-2. (DSE-46535)
  • Resolved an issue that prevented registries in renew:finished status from being used by Cloudera AI Inference service. Upgrading Cloudera AI Inference service is required to use these registries. (DSE-46815)
  • Previously, the UI would flicker when trying to access the Registered Models UI due to an issue. This issue is now resolved. (DSE-46714)
  • Resolved a critical bug that caused cdh-client to restart in a workbench, which prevented sessions from starting. (DSE-46989)
Cloudera AI Workbench
  • Previously, users were unable to register models from within Cloudera AI Workbenches. This issue is now resolved. Upgrading workbenches is required to register models from within Cloudera AI Workbenches . (DSE-46656)