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Since launching in 2018, MLflow has been one of the major open-source tools in managing machine learning lifecycles. In the previous edition, we discussed the machine learning lifecycle and how to use MLflow to track experiments. Since MLflow 3.0, the community as well as Databricks has successfully evolved MLflow to support various GenAI use cases, from the basics like prompt versioning to agent tracing to custom judges.

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MLflow 3 and the GenAI Agents

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Jason Yip,
  • Nikhil Gupta,
  • Marcin Wojtyczka

摘要

Since launching in 2018, MLflow has been one of the major open-source tools in managing machine learning lifecycles. In the previous edition, we discussed the machine learning lifecycle and how to use MLflow to track experiments. Since MLflow 3.0, the community as well as Databricks has successfully evolved MLflow to support various GenAI use cases, from the basics like prompt versioning to agent tracing to custom judges.