MLflow 2.22 Release

[Tomu Hirata]

Hi, all. We are excited to announce that we just released MLflow 2.22.0.
This release brings important bug fixes and improvements for the UI and tracking capabilities:

Supported tracing for OpenAI Responses API (#15240, @B-Step62)
Introduced get_last_active_trace, which affects model serving/monitoring logic (#15233, @B-Step62)
Introduced async export for Databricks traces (default behavior) (#15163, @B-Step62)
Added Gemini embeddings support with corresponding unit tests (#15017, @joelrobin18)
MySQL SSL connections are now supported with client certs (#14839, @aksylumoed)
Added Optuna storage utility for enabling parallel hyperparameter tuning (#15243, @XiaohanZhangCMU)
Added support for Azure Data Lake Storage (ADLS) artifact repositories (#14723, @serena-ruan)
Artifact views for text now auto-refresh in the UI (#14939, @joelrobin18)

Please visit the release notes for more details.

Kind regards,

MLflow Maintainers