MLflow 2.22.0 brings important bug fixes and improvements to the UI and tracking capabilities.

Features:

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

Bug Fixes:

• [Tracking / UI] Fixed serialization for structured output in langchain_tracer + added unit tests.
  (#14971, @joelrobin18)
• [Server-infra] Enforced password validation for authentication (min. 8 characters).
  (#15287, @WeichenXu123)
• [Deployments] Resolved an issue with the OpenAI Gateway adapter.
  (#15286, @WeichenXu123)
• [Artifacts / Tracking / Server-infra] Normalized paths by stripping trailing slashes.
  (#15016, @tarek7669)
• [Tags] Fixed a bug where tag values containing ": " were being truncated.
  (#14896, @harupy)

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.