Pipelines SDK

Information about the Kubeflow Pipelines SDK

Introduction to the Pipelines SDK

Overview of using the SDK to build components and pipelines

Install the Kubeflow Pipelines SDK

Setting up your Kubeflow Pipelines development environment

Connect the Pipelines SDK to Kubeflow Pipelines

How to connect the Pipelines SDK to Kubeflow Pipelines in various ways

Build a Pipeline

A tutorial on building pipelines to orchestrate your ML workflow

Building Components

A tutorial on how to create components and use them in a pipeline

Building Python function-based components

Building your own lightweight pipelines components using Python

Best Practices for Designing Components

Designing and writing components for Kubeflow Pipelines

Pipeline Parameters

Passing data between pipeline components

Visualize Results in the Pipelines UI

Visualizing the results of your pipelines component

Pipeline Metrics

Export and visualize pipeline metrics

DSL Static Type Checking

Statically check the component I/O types

DSL Recursion

Author a recursive function in DSL

Using environment variables in pipelines

How to set and use environment variables in Kubeflow pipelines

GCP-specific Uses of the SDK

SDK features that are available on Google Cloud Platform (GCP) only

Kubeflow Pipelines SDK for Tekton

How to run Kubeflow Pipelines with Tekton

Manipulate Kubernetes Resources as Part of a Pipeline

Overview of using the SDK to manipulate Kubernetes resources dynamically as steps of the pipeline

Python Based Visualizations (Deprecated)

Predefined and custom visualizations of pipeline outputs


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Last modified September 15, 2022: Pipelines v2 content: KFP SDK (#3346) (3f6a118c)