Installation guide
Kedro setup
First, you need to install base Kedro package
$ pip install 'kedro'
Plugin installation
Install from PyPI
You can install kedro-vertexai
plugin from PyPi
with pip
:
pip install --upgrade kedro-vertexai
Install from sources
You may want to install the develop branch which has unreleased features:
pip install git+https://github.com/getindata/kedro-vertexai.git@develop
Available commands
You can check available commands by going into project directory and runnning:
$ kedro vertexai
Usage: kedro vertexai [OPTIONS] COMMAND [ARGS]...
Interact with GCP Vertex AI Pipelines
Options:
-e, --env TEXT Environment to use.
-h, --help Show this message and exit.
Commands:
compile Translates Kedro pipeline into YAML file with Kubeflow...
init Initializes configuration for the plugin
list-pipelines List deployed pipeline definitions
run-once Deploy pipeline as a single run within given experiment.
schedule Schedules recurring execution of latest version of the...
ui Open Kubeflow Pipelines UI in new browser tab
upload-pipeline Uploads pipeline to Kubeflow server
init
init
command takes one argument (that is the kubeflow pipelines root url) and generates sample
configuration file in conf/base/vertexai.yaml
. The YAML file content is described in the
Configuration section.
ui
ui
command opens a web browser pointing to the currently configured VertexAI Pipelines UI on GCP web console.
list-pipelines
list-pipelines
uses Kubeflow Pipelines to retrieve all registered pipelines
compile
compile
transforms Kedro pipeline into Vertex AI workflow. The
resulting yaml
file can be uploaded to Vertex AI Pipelines via web UI.
run-once
run-once
is all-in-one command to compile the pipeline and run it in the GCP Vertex AI Pipelines environment.