Create and Manage SageMaker Pipelines
You can use Amazon SageMaker Model Building Pipelines to create end-to-end workflows that manage and deploy SageMaker jobs. SageMaker Pipelines comes with SageMaker Python SDK integration, so you can build each step of your pipeline using a Python-based interface.
After your pipeline is deployed, you can view the directed acyclic graph (DAG) for your pipeline and manage your executions using Amazon SageMaker Studio. Using SageMaker Studio, you can get information about your current and historical pipelines, compare executions, see the DAG for your executions, get metadata information, and more. To learn how to view pipelines from SageMaker Studio, see View, Track, and Execute SageMaker Pipelines in SageMaker Studio.
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