MLflow 3.6.0 Release

[Yuki Watanabe]

Hi all! We are exicited to annouce the availability of MLflow 3.6.0 with tons of new features and enhancement🚀

Full release post: https://mlflow.org/releases/3.6.0  

#1: Full OpenTelemetry Support in MLflow Tracking Server
MLflow now offers comprehensive OpenTelemetry integration, allowing you to use OpenTelemetry and MLflow seamlessly together for your observability stack, including mutual trace ingestion. See blog post for more details and how to set it up!

#2: Session-level View in Trace UI

New chat sessions tab provides a dedicated view for organizing and analyzing related traces at the session level, making it easier to track conversational workflows. See the Track Users & Sessions guide for more details.

#3: New Supported Frameworks in TypeScript Tracing SDK

Auto-tracing support for Vercel AI SDK, Mastra, Anthropic SDK, Gemini SDK in TypeScript, expanding MLflow's observability capabilities across popular JavaScript/TypeScript frameworks. For more information, please check out the TypeScript Tracing SDK.

#4: Tracking Judge Cost and Traces

Comprehensive tracking of LLM judge evaluation costs and traces, providing visibility into evaluation expenses and performance with automatic cost calculation and rendering. See LLM Evaluation Guide for more details!

#5: New experiment tab bar

The experiment tab bar has been fully overhauled to provide more intuitive and discoverable navigation of different features in MLflow. Upgrade to MLflow 3.6.0 to try it out!

#6: Agent Server for Lightning Agent Deployment

New agent server infrastructure for managing and deploying scoring agents with enhanced orchestration capabilities. See Agent Server Guide for more details.

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