Pipeline Metrics

Export and visualize pipeline metrics

Out of date

This guide contains outdated information pertaining to Kubeflow 1.0. This guide needs to be updated for Kubeflow 1.1.

This page shows you how to export metrics from a Kubeflow Pipelines component. For details about how to build a component, see the guide to building your own component.

Overview of metrics

Kubeflow Pipelines supports the export of scalar metrics. You can write a list of metrics to a local file to describe the performance of the model. The pipeline agent uploads the local file as your run-time metrics. You can view the uploaded metrics as a visualization in the Runs page for a particular experiment in the Kubeflow Pipelines UI.

Export the metrics file

To enable metrics, your component must write a JSON file specifying metrics to render. The pipeline component must also export a file output artifact with an artifact name of mlpipeline-metrics, or else the Kubeflow Pipelines UI will not render the visualization. In other words, the .outputs.artifacts setting for the generated pipeline component should show: - {name: mlpipeline-metrics, path: /mlpipeline-metrics.json}. The JSON filepath does not matter, although /mlpipeline-metrics.json is used for consistency in the examples below.

Example JSON content:

  1.   accuracy = accuracy_score(df['target'], df['predicted'])
  2.   metrics = {
  3.     'metrics': [{
  4.       'name': 'accuracy-score', # The name of the metric. Visualized as the column name in the runs table.
  5.       'numberValue':  accuracy, # The value of the metric. Must be a numeric value.
  6.       'format': "PERCENTAGE",   # The optional format of the metric. Supported values are "RAW" (displayed in raw format) and "PERCENTAGE" (displayed in percentage format).
  7.     }]
  8.   }
  9.   with file_io.FileIO('/mlpipeline-metrics.json', 'w') as f:
  10.     json.dump(metrics, f)

See the full example.

The metrics file has the following requirements:

  • name must follow the pattern ^[a-zA-Z]([-_a-zA-Z0-9]{0,62}[a-zA-Z0-9])?$.

    For Kubeflow Pipelines version 0.5.1 or earlier, name must match the following pattern ^[a-z]([-a-z0-9]{0,62}[a-z0-9])?$

  • numberValue must be a numeric value.

  • format can only be PERCENTAGE, RAW, or not set.

View the metrics

To see a visualization of the metrics:

  1. Open the Experiments page in the Kubeflow Pipelines UI.
  2. Click one of your experiments. The Runs page opens showing the top two metrics, where top is determined by prevalence (that is, the metrics with the highest count) and then by metric name. The metrics appear as columns for each run.

The following example shows the accuracy-score and roc-auc-score metrics for two runs within an experiment:

Metrics from a pipeline run

Next step

Visualize the output of your component by writing out metadata for an output viewer.

Last modified 29.09.2020: Correct requirement inaccuracy in the metrics documentation (#2213) (ecdb4f04)