When Autolog Stops Logging — Fabric Experiments

When Autolog Stops Logging Episode 23 • 2026-06-05 Duration: 8:47 Fabric's MLflow autologging promises zero-effort experiment tracking — until you train with LightGBM or XGBoost and discover your metrics column is blank. We pull apart the framework gap, the compounding exclusive flag, and the Git backup that isn't one. What we discuss How it actually works underneath the abstraction Where the obvious answer breaks A real Reddit/Microsoft Q&A question unpacked The pattern we keep seeing in the field Risks of the recommended path F-SKU realism — what this actually costs When the rejected approach is actually right The concrete recommended architecture The architectural principle to take home Key takeaways Somewhere right now, a training run just finished. And name your runs. Pass run_name to start_run. Forty runs all called Run followed by a number, and the comparison pane becomes useless regardless of how clean the rest of your tracking is. The takeaway I'd leave anyone starting with Fabric Experiments — the abstraction is real, but it has seams you need to know on day one. Resources mlflow-upgrade Machine learning experiments in Microsoft Fabric Autologging in Microsoft Fabric What is Data Science in Microsoft Fabric? Analyze and train data in Microsoft Fabric Hyperparameter tuning in Fabric Perform hyperparameter tuning with FLAML Training visualizations for AutoML MLflow 3 in Fabric Data Science Tutorial: Create, evaluate, and score a churn prediction model Tutorial Part 3: Train and register a machine learning model Train models with scikit-learn in Microsoft Fabric Machine learning experiments and models Git integration and deployment pipelines (Preview) Data science roles and permissions Lineage for models and experiments About the show AI-generated voices. Matthias — cloned voice. Fabia — designed AI co-host. See Matthias live on YouTube (Fabric Friday), at his meetups, and at conferences like FabCon. Hosted by Matthias Falland — Microsoft Data Platform MVP and community architect behind the Fabric Periodic Table. New episodes every Friday. Submit your case Have an architecture decision you are wrestling with? DM Matthias on LinkedIn — find him as Matthias Falland. Three to five sentences about the decision, your team size, and your current stack. We anonymize before airing. This podcast was generated by AI. Brand design based on fabricperiodictable.com.