Introduction to the Pipelines Interfaces

This page introduces the interfaces that you can use to build and runmachine learning (ML) workflows with Kubeflow Pipelines.

You can access the Kubeflow Pipelines UI by clicking Pipeline Dashboard onthe Kubeflow UI. The Kubeflow Pipelines UI looks like this:

• Run one or more of the preloaded samples to try out pipelines quickly.
• Upload a pipeline as a compressed file. The pipeline can be one that youhave built (see how to build apipeline) or onethat someone has shared with you.
• Create and start a run within the experiment. A run is a single executionof a pipeline. See the .
• Explore the configuration, graph, and output of your pipeline run.
• Schedule runs by creating a recurring run.

See the quickstart guide for moreinformation about accessing the Kubeflow Pipelines UI and running the samples.

When building a pipeline component, you can write out information for displayin the UI. See the guides to and visualizing results inthe UI.

See the for an overview of the ways you canuse the SDK to build pipeline components and pipelines.

The Kubeflow Pipelines API is useful for continuous integration/deploymentsystems, for example, where you want to incorporate your pipeline executionsinto shell scripts or other systems.For example, you may want to trigger a pipeline run when new data comes in.