The main thing we try to help with is orchestrating Spark, TensorFlow, TensorFlow Serving, and other workloads without requiring you to manage the infrastructure. You’re right that we have a thin layer around tf.estimator (by design) because our goal is to make it easy to create scalable and reproducible pipelines from building blocks that people are familiar with. We translate the YAML blocks into workloads that run as a DAG on Kubernetes behind the scenes.
