The migration broke in ways the docs never mentioned
Kubeflow Pipelines promises "Airflow but cloud-native." The reality? I spent three days fixing silent failures that wouldn't happen in Airflow.
The switch isn't just about rewriting DAGs as Python functions. Three specific breaking changes caught me off-guard, and none of them showed up in the official migration guides. Here's what actually breaks when you move from Airflow to Kubeflow, with the exact errors and fixes.
Task dependencies behave completely differently
In Airflow, if Task B depends on Task A, and A fails, B simply doesn't run. The DAG stops, you get a notification, life goes on.
Kubeflow Pipelines doesn't work this way.
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