Release NotesPDF version

What's New

Major features and updates for the Cloudera AI data service.

Release notes and fixed issues for version 2.0.47-b360.

Cloudera AI Workbench
  • Previously, when users try to create a session, the ssh: This private key is passphrase protected error was displayed. This issue is now resolved. (DSE-426980)

Release notes and fixed issues for version 2.0.47-b359.

Cloudera AI Platform

  • We have improved the synchronization efficiency and ease of use of the user management and team management auto synchronization features. The major updates include:

    • Auto-synchronization is enabled by default: Auto synchronization for users and teams is now enabled by default, with a synchronization interval set to 12 hours.
    • User management service: User management is now handled by a new service, reducing overhead on the web pod. It now prevents multiple synchronization operations from running in parallel.
    • Logging: Detailed logging has been added for the failure cases.
    • Synchronization trigger sequence: The team synchronization now internally triggers user synchronization to pull the most recent user details from the Cloudera control plane.

    These improvements are aimed at optimizing performance and streamlining the synchronization process for users and teams. (DSE-37941)

  • We have added support to set maximum input/output operations per second (IOPS) and throughput for root volumes attached to worker nodes, using the UI while provisioning a workbench. Note, that this is supported only for AWS. For more details on how to Maximize IOPS and throughput of the root volumes, see Provisioning Cloudera AI Workbenches. (DSE-42075)
Cloudera AI Registry
  • You can now specify subnets for load balancers when creating the AI Registry. (DSE-42156)
  • We have enhanced the security of the AI Registry's search capability. (DSE-41740)
Cloudera AI Inference service
  • We have improved the UI usability of the Hugging Face import feature by adding a tooltip example. (DSE-41926)
Cloudera AI Workbench
  • We have increased Grafana pod's default memory and CPU to prevent from out of memory (OOM) errors. (DSE-39525)
  • We have increased the Remote Procedure Call (GRPC) Operator timeout to two minutes to prevent from errors encountered with 150 concurrent sessions. (DSE-36922)
  • We have removed unessential calls to the usage API to resolve slowness during new workload creation under heavy load in a workbench. (DSE-42231)
Cloudera AI Platform
  • We have optimized the Suspend timeout during periods of high network latency. (DSE-42055)
  • Previously, when restoring a workbench with a very large Elastic File System (EFS) drive was failing due to session time out. This issue is now resolved. (DSE-42171)
Cloudera AI Registry
  • We have fixed an issue that prevented from model registration to the AI Registry within a workbench. (DSE-42360)
  • We have fixed a page token issue that prevented users from viewing AI Registry models on subsequent pages within the workbench. (DSE-42379)
  • We have fixed an incorrect error message displayed in the UI when deleting AI Registry models from within a workbench. (DSE-42379)
  • Error visibility has been improved during AI Registry backup. (DSE-42163)
Cloudera AI Inference service
  • We have fixed an issue that prevented from rendering TPOT (Time per Output Token) and TTFT (Time to First Token) charts for Hugging Face models. (DSE-42192)
ML Runtimes
  • Previously, non-administrator users were unable to add new Runtimes to the Runtime Catalog. This issue is now resolved. (DSE-42298)

Release notes and fixed issues for version 2.0.47-b345.

Cloudera AI Workbench
  • Support is now provided for API keys to invoke applications deployed using Cloudera AI Workbenches. This not only eases the invocation of those applications programmatically but also allows one application to easily invoke another application that they have access to.
  • MLFLOW upgrade for Cloudera AI Workbenches now enables making use of the latest offerings and APIs from the MLFLOW community like evaluateLLM.
Cloudera AI Platform
  • The autoscaling range of Suspend Workflow is now set to the value 0 to ensure that other Kubernetes deployments outside the scope of MLX can deploy their pods on worker nodes.
Cloudera AI Registry
  • An enhanced error message is now displayed during model upload failure.
  • UI for Registered Models displays the environment name of the registry along with an error message when any user is unable to access any Cloudera AI Registry.
  • A checkbox is now added to enable Public Load Balancer for new Cloudera AI Registries on Azure.
Cloudera AI Inference service
  • The Hugging Face model server backend has been upgraded, which expands the compatibility with a larger number of model families, such as Llama 3.3 and models derived from it.
  • Llama 3.2 Vision Language Model NIM version has been updated to address compatibility with A10G (g5.*) and L40S (g6e.*) GPU instances on AWS.
  • You can now upgrade Cloudera AI Inference service using the UI. Previously, the upgrade was supported only using CDPCLI.
  • You can now upgrade from Cloudera AI Inference service version 1.2.0-b80 to version 1.3.0-b113 or higher. Note that you cannot upgrade from 1.3.0-b111 to 1.3.0-b113 or higher. For more information on the 1.3.0-b111 upgrade issue and workaround, see the Known Issues section.
Cloudera AI Workbench
  • Previously, due to an issue, users could stop sessions under projects that they were not authorized to access using the session’s UUID. This issue is now resolved. (DSE-39798)
  • Previously, when a Kubernetes object was deleted, and the reconciler was overwhelmed by a large number of events, the Deleted status failed to propagate properly. This issue is now resolved. (DSE-41431)
  • Previously, the stopped_at column was not correctly populated when applications were stopped. This issue is now resolved. (DSE-41636)
  • Previously, engine pods were stuck in the Init:StartError state and you had to manually delete it. With this fix, pods stuck in Init:StartError in the Garbage Collection will be deleted after a certain grace period. (DSE-41430)
  • Previously, Spark environment configurations were not inherited by models running Spark. With this fix, models use the appropriate Spark configurations to run Spark. (DSE-36343)
Cloudera AI Registry
  • An issue around how Hugging Face token was being consumed during the import of a model was addressed. (DSE-41714)
  • The Cloudera AI Registry deletion flow is improved to take care of race conditions when both creation and deletion are triggered in a short frame of time. (DSE-41634)
Cloudera AI Inference service
  • Previously, the GetEndpointLogs failed with an error. With this fix, endpoint logs for the model container do not exceed the gRPC messaging size. (DSE-41765)
  • A new field called loadBalancerIPWhitelists is added to display a list of IPs whitelisted for the load balancer and deprecated isPublic and ipAllowlist. (DSE-39397)
  • Infrastructure nodes are no longer shown as instances that can be used for deploying a new endpoint. (DSE-41726)
ML Runtimes
  • Previously, due to an issue, to ensure the compatibility of AMPs with ML Runtimes 2025.01.1, users had to switch to JupyterLab PBJ Workbench in the AMPs’ .project-metadata.yaml file or use jobs instead of sessions for automated tasks. This issue is now resolved. (DSE-41263)
  • Resolved issues related to using R interactively in PBJ Runtimes. (DSE-41771)

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