title: Kubeflow vs Vertex AI Pipelines
body: <p>I was exploring kubeflow pipelines and Vertex AI pipelines. From what I understand, Vertex AI pipelines is a managed version of kubeflow pipelines so one doesn't need to deploy a full fledged kubeflow instance. In that respect, pricing aside, Vertex AI pipelines is a better choice. But then, in kubeflow, one can create <a href="https://www.kubeflow.org/docs/components/pipelines/concepts/experiment/" rel="noreferrer">experiments</a>, an equivalent for which I have not found in Vertex AI pipelines. The only kubeflow features that Vertex AI does not support that I have been able to spot in the <a href="https://cloud.google.com/vertex-ai/docs/pipelines/migrate-kfp#features_not_supported_in" rel="noreferrer">documentation</a> are &quot;Cache expiration&quot; and &quot;Recursion&quot; but they do not mention anything about experiments. Makes me wonder if there are other differences that are worth considering when deciding between the two.</p>