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.