- Building Pipelines with the SDK
- Introduction to the Pipelines SDK
- Install the Kubeflow Pipelines SDK
- Build Components and Pipelines
- Create Reusable Components
- Build Lightweight Python Components
- Best Practices for Designing Components
- Pipeline Parameters
- Python Based Visualizations
- Visualize Results in the Pipelines UI
- Pipeline Metrics
- DSL Static Type Checking
- DSL Recursion
- GCP-specific Uses of the SDK
- Manipulate Kubernetes Resources as Part of a Pipeline
Building Pipelines with the SDK
Use the Kubeflow Pipelines SDK to build components and pipelines
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
Build Components and Pipelines
Building your own component and adding it to a pipeline
Create Reusable Components
A detailed tutorial on creating components that you can use in various pipelines
Build Lightweight Python Components
Building your own lightweight pipelines components from Python
Best Practices for Designing Components
Designing and writing components for Kubeflow Pipelines
Pipeline Parameters
Passing data between pipeline components
Python Based Visualizations
Predefined and custom visualizations of pipeline outputs
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
GCP-specific Uses of the SDK
SDK features that are available on Google Cloud Platform (GCP) only
Manipulate Kubernetes Resources as Part of a Pipeline
Overview of using the SDK to manipulate Kubernetes resources dynamically as steps of the pipeline