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For Self-Managed AI Platform users running v11.1, see the on-premise platform documentation
AI Platform releases > Self-Managed releases > Version 11.1.x > V11.1 maintenance releases > V11.1.8

V11.1.8

April 24, 2026

The DataRobot Self-Managed AI Platform v11.1.8 release, part of DataRobot's continual effort to secure the product and platform, addresses issues reported in earlier releases. See also the features introduced in v11.1.0, released July 17, 2025.

Issues fixed in V11.1.8:

The following issues have been fixed since release v11.1.7:

Modeling

  • MODEL-23003: Updated NextGen Edit Blueprint training to handle OTV projects by adding the blueprint to the project menu and submitting training via a GET /datetimeModel request.
  • MODEL-21300: Added a Blueprint ID to models prepared for deployment with frozen parameters.

Platform

  • FLEET-4956: The datarobot helm plugin was updated with new flags, --upgrade-from and --no-upgrade, for the images, sync, and save commands to exclude images from the manifest that are only needed during upgrades from specific versions.
  • CMPT-4847: Previously, when image builder pods were terminated due to resource constraints, builds could remain stuck in a non-terminal state for 4+ hours. This change improved pod monitoring to detect missing builder pods within ~15 minutes and immediately mark the build as FAILED. A 5-minute grace period prevents false failures for newly created builds while ensuring rapid detection of evicted pods. This change significantly reduces build failure detection time and improves overall system responsiveness.

Data

  • DM-20657: DataRobot Python client v3.8.4: Fixed deserialization of {class}ProjectOptions <datarobot.models.project_options.ProjectOptions> when loading project options from the server: feature_engineering_prediction_point, user_partition_col, and each entry in external_predictions are column names returned as strings by the API (the client previously expected {class}Feature <datarobot.models.feature.Feature>-shaped data, which could raise validation errors).

Notebooks

  • CFX-5599: Fixed an issue where notebook kernel trace data was not collected. Added network policy to enable communication with the OpenTelemetry collector.

Notices

SageMaker will no longer be pre-installed in Python kernels. If you use SageMaker:

  • In your notebook or codespace use: !pip install sagemaker
  • Use a custom environment with Sagemaker pinned.

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