v3.16.0·MLflow 3.16.0
Summary
MLflow 3.16.0 makes the redesigned trace explorer the default interface, introducing natural-language custom trace views via the MLflow Assistant, session grouping for multi-turn conversations, and span links. The update also adds Unity Catalog model service support for built-in evaluation judges, per-user AI Gateway budget policies, and fail-closed authorization by default.
Summary generated by brickster.ai. For the full changelog and any code/binary attachments, follow the GitHub link above.
More from mlflow/mlflow
MLflow 3.17.0
MLflow 3.17.0 introduces fine-grained access control for runs and traces, links evaluation metrics directly to managed datasets, and adds support for Databricks Unity Catalog model service resources. Self-hosted SQL tracking servers require a coordinated schema migration via mlflow db upgrade with all writers stopped, as rolling deployments are not supported.
MLflow 2.11.5
Users can now opt in to route Unity Catalog model registry artifact uploads and downloads through the Databricks SDK Files API. This update provides an alternative transfer mechanism for managing model artifacts within Databricks environments.
MLflow 3.16.1
MLflow 3.16.1 removes the default basic-auth admin password from basic_auth.ini as a security fix (GHSA-gq3w-7jj3-x7gr) and adds support for span links in Unity Catalog traces. The release also fixes trace location resolution in Databricks Model Serving, includes a timeout option for the @scorer decorator, and improves web UI access control for non-admin users.
MLflow 3.15.2 introduces immutable evaluation dataset versions and a scorer_ensemble primitive for combining scorer results. The patch also fixes a Databricks telemetry deadlock and addresses issues in MemAlign aligned judges and runs.status constraint handling.
MLflow 3.15.1
MLflow 3.15.1 fixes version parsing issues on Databricks Serverless and corrects env_pack behavior on ARM client images. Scorer versioning documentation has been clarified.
MLflow 3.15.0 introduces an MCP Registry for registering and sharing Model Context Protocol servers, enhances the Assistant with multi-provider LLM support and per-session token usage tracking, and enables proxy-less artifact transfers via presigned URLs to reduce server load and timeouts on large files. Additional improvements include sharable Runs table views, multi-modal image attachments for LLM judges to evaluate vision tasks, and numerous bug fixes across tracing, evaluation, gateway, and UI components.