#767 mlflow integration Pull request opened by samhita-alla Summary • New

flyteplugins-mlflow

plugin that integrates MLflow experiment tracking with Flyte tasks via a

@mlflow_run

decorator • Supports automatic run management, autologging, parent/child run sharing, nested runs (cross-container), distributed training (rank-gated logging), and auto-generated MLflow UI links • Includes configuration management via

mlflow_config()

for workflow-level defaults and per-task overrides Run modes •

auto

(default): Reuse parent's MLflow run if available, otherwise create a new one • `new`: Always create an independent run • `nested`: Create a new run with

mlflow.parentRunId

tag linking it to the parent. This works across tasks without needing the parent run active in the same process. Key features • Autologging:

@mlflow_run(autolog=True, framework="sklearn")

enables MLflow autologging with optional framework targeting • Distributed training: Auto-detects

RANK

env var; only rank 0 logs to MLflow • Link auto-generation:

mlflow_config(link_host=...)

generates MLflow UI URLs that propagate to child tasks with

links=(Mlflow(),)

• Local execution: Handles MLflow's active run stack correctly when parent and child tasks share a process flyteorg/flyte-sdk