+++ title = "Pipeline Metrics" description = "Export and visualize pipeline metrics" weight = 9 +++ This page shows you how to export metrics from the component. For details about how to build a component, see the guide to [building your own component](/docs/pipelines/sdk/build-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 experiment runs page in the Kubeflow Pipelines UI. ## Export the metrics file To enable metrics, your program must to write a file `/mlpipeline-metrics.json`. For example: ```Python accuracy = accuracy_score(df['target'], df['predicted']) metrics = { 'metrics': [{ 'name': 'accuracy-score', # The name of the metric. Visualized as the column name in the runs table. 'numberValue': accuracy, # The value of the metric. Must be a numeric value. 'format': "PERCENTAGE", # The optional format of the metric. Supported values are "RAW" (displayed in raw format) and "PERCENTAGE" (displayed in percentage format). }] } with file_io.FileIO('/mlpipeline-metrics.json', 'w') as f: json.dump(metrics, f) ``` See the [full example](https://github.com/kubeflow/pipelines/blob/master/components/local/confusion_matrix/src/confusion_matrix.py#L90). There are several conventions for the metrics file: * The file path must be `/mlpipeline-metrics.json`. * The name must follow the pattern `^[a-z]([-a-z0-9]{0,62}[a-z0-9])?$`. * The format can only be `PERCENTAGE`, `RAW` or not set. * `numberValue` must be a numeric value. ## Visualize the metrics To see a visualization of the metrics, open the **Experiments** page in the Kubeflow Pipelines UI, and select an experiment. The UI shows the top three metrics as columns for each run. The following example shows two metrics, **accuracy-score** and **roc-auc-score**. Click **Compare runs** to display the full metrics. <img src="/docs/images/metric.png" alt="Run metrics" class="mt-3 mb-3 border border-info rounded">