2026
- January 22 - Introducing MLflow Agents Dashboard
- January 29 - Introducing DeepEval, RAGAS, and Phoenix Judges in MLflow
- February 3 - MemAlign: Building Better LLM Judges From Human Feedback With Scalable Memory
- February 9 - 5 Tips to Get More Out of Your Claude Code with MLflow
- February 24 - Multi-turn Evaluation & Simulation: Enhancing AI Observability with MLflow for Chatbots
- February 24 - Introducing MLflow AI Gateway: Governed, Observable Access to LLMs
- February 26 - Enterprise-Scale MLflow Operations and Security Practices at LY Corporation
- February 27 - Ship LLM Agents Faster with Coding Assistants and MLflow Skills
- March 2 - Benchmark Your Way to Better RAG and Agents:Tuning Vector Search with MLflow
- March 4 - Agent Trace Evaluation with TruLens Scorers in MLflow
2025
- January 23 - From Natural Language to SQL: Building and Tracking a Multi-Lingual Query Engine
- January 30 - Beyond Autolog: Add MLflow Tracing to a New LLM Provider
- March 6 - Practical AI Observability: Getting Started with MLflow Tracing
- April 1 - Automatically find the bad LLM responses in your LLM Evals with Cleanlab
- April 28 - MLflow Go
- May 4 - Tracking Image Datasets with MLflow
- June 9 - Announcing MLflow 3
- July 24 - MLflow Meets TypeScript: Debug and Monitor Full-Stack AI Applications with MLflow
- August 11 - Assessment-focused UIs in MLflow
- August 30 - Building and Managing an LLM-based OCR System with MLflow
- September 15 - Beyond Manually Crafted LLM Judges: Automate Building Domain-Specific Evaluators with MLflow
- October 15 - Rapidly Prototype and Evaluate Agents with Claude Agent SDK and MLflow
- October 27 - Systematic Prompt Optimization for OpenAI Agents with GEPA
- November 5 - Full OpenTelemetry Support in MLflow Tracing
- December 24 - AI Observability for Every TypeScript LLM Stack
2024
- January 23 - Custom MLflow Models with mlflow.pyfunc
- January 25 - Streamline your MLflow Projects with Free Hosted MLflow
- January 26 - 2023 Year in Review
- March 5 - Announcing MLflow Enhancements - Deep Learning with MLflow (Part 1)
- April 17 - MLflow Release Candidates
- April 26 - Deep Learning with MLflow (Part 2)
- June 10 - Introducing MLflow Tracing
- July 26 - PyFunc in Practice
- August 6 - LangGraph with Model From Code
- August 29 - AutoGen with Custom PyFunc
- September 13 - Models from Code Logging in MLflow - What, Why, and How
- October 3 - LLM as judge
- October 25 - Building Advanced RAG with MLflow and LlamaIndex Workflow
- November 7 - Using Bedrock Agent as an MLflow ChatModel with Tracing
- December 20 - MLflow Tracing in Jupyter Notebooks