Vertex AI Pipelines lets you run machine learning (ML) pipelinesthat were built using the Kubeflow Pipelines SDK or TensorFlow Extended in a serverlessmanner. This document describes how to use Vertex AI Pipelines tovisualize, analyze, and compare pipeline runs.

To learn more about running and scheduling pipelines, read the guide torunning a pipeline.

Visualize pipeline runs using Google Cloud console

Use the following instructions to learn more about using Google Cloud console tovisualize pipeline runs.

1. Open Vertex AI Pipelines in Google Cloud console.

   Go to Vertex AI Pipelines

2. InSelect a recent project, click a project tile.

3. Click the run name of the pipeline run that you want to analyze.

   The pipeline run page appears and displays the pipeline's runtime graph.The pipeline's summary appears in thePipeline run analysis pane.

   • The pipeline graph shows the workflow steps in the pipeline.
   • The pipeline summary shows the basic information about the pipeline runand the parameters that were used in this pipeline run.

4. To learn more about a pipeline step or artifact, click the step or artifactin the runtime graph.

   ThePipeline run analysis pane shows information about this pipelinestep or artifact.

   • For pipeline steps, this information includes execution details, theinput parameters that were passed to the step, and any output parametersthat the step passed to the pipeline.

     To learn more about the selected pipeline step:

     • ClickView job to see the job details.

       The job details page includes information like the machine type usedto run this step, the container image that the step runs in, and theencryption key used by this step.

     • ClickView logs to see the logs produced by this pipeline step.

       The logs pane appears. Use the logs to help debug the behavior ofyour pipeline.

   • For artifacts, this information includes the data type of the artifact,the location where the artifact is stored, and the artifact's metrics.

     To learn more about the selected artifact:

     • Click the artifact'sURI to open that location in Cloud Storage.

     • ClickOpen in ML Metadata to view the lineage of the artifact inVertex ML Metadata. For more information about pipelineartifact lineage, seeTrack the lineage of pipeline artifacts.If you're new to Vertex ML Metadata, read theintroduction to Vertex ML Metadata.

Compare pipeline runs using Google Cloud console

Use the following instructions to compare pipeline runs in Google Cloud console.

1. Open Vertex AI Pipelines in Google Cloud console.

   Go to Vertex AI Pipelines

2. Select the checkboxes of the pipeline runs that you want to compare.

3. In the Vertex AI Pipelines menubar, clickcompare_arrowsCompare.

   TheCompare runs pane appears.

4. TheCompare runs pane lists your pipeline's parameters and metrics.

   This information helps you to perform analysis, such as analyzing howdifferent sets of hyperparameters affect a model's metrics.

What's next

• Read theintroduction to Vertex AI Pipelines to learnmore about orchestrating ML workflows.
• Learn how tobuild a machine learning pipeline.