Kubeflow Pipelines - GitOps Repository

This repository contains ML pipeline definitions managed via ArgoCD.

Structure

.
├── pipelines/           # Pipeline Python definitions
│   └── examples/        # Example pipelines
├── components/          # Reusable pipeline components
├── experiments/         # Experiment configurations
├── runs/               # Scheduled/triggered runs
└── manifests/          # K8s manifests for ArgoCD

Usage

1. Add a pipeline: Create a Python file in pipelines/
2. Push to main: ArgoCD auto-deploys
3. Monitor: Check Kubeflow UI at <KUBEFLOW_URL>

Quick Start

from kfp import dsl

@dsl.component
def hello_world() -> str:
    return "Hello from Kubeflow!"

@dsl.pipeline(name="hello-pipeline")
def hello_pipeline():
    hello_world()

Environment

• Kubeflow: <KUBEFLOW_URL>
• MinIO: <MINIO_URL>
• ArgoCD: <ARGOCD_URL>