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Clarify KFP getting started endpoint setup #4380

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Clarify KFP getting started endpoint setup #4380

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8 changes: 7 additions & 1 deletion content/en/docs/components/pipelines/getting-started.md
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Expand Up @@ -44,7 +44,7 @@ You can submit the YAML file to a KFP-conformant backend for execution. If you h
```python
from kfp.client import Client

client = Client(host='<MY-KFP-ENDPOINT>')
client = Client(host='http://localhost:3000')
run = client.create_run_from_pipeline_package(
'pipeline.yaml',
arguments={
Expand All @@ -53,6 +53,12 @@ run = client.create_run_from_pipeline_package(
)
```

Replace `http://localhost:3000` with the endpoint for your Kubeflow Pipelines deployment. For a local standalone deployment, port-forward the `ml-pipeline-ui` service first:

```sh
kubectl port-forward --namespace kubeflow svc/ml-pipeline-ui 3000:80
```

The client will print a link to view the pipeline execution graph and logs in the UI. In this case, the pipeline has one task that prints and returns `'Hello, World!'`.

## Next steps
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