kfp

Components that I have created for Kubeflow Pipelines. Try them in https://cloud-pipelines.net/pipeline-editor/

A collection of awesome examples and tips regarding KubeFlow Pipeline.

Everything to get industrial kubeflow applications running in production

Scan all Kubeflow pipelines for exposed secrets

The toolbox for kfp (Kubeflow Pipelines SDK)

An enterprise-grade RAG Chatbot built with AI-assisted development. Features local LLMs (Ollama), LlamaIndex integration, and Entra ID SSO. Designed for secure, air-gapped PDF analysis. 📄

3-stage Kubeflow Pipelines (KFP v2) ML pipeline on Vertex AI: BigQuery extraction → feature engineering → scikit-learn model training with full artifact lineage tracking. Components run in isolated Docker containers.

My fork of Kubeflow — end-to-end ML workflow orchestration on Kubernetes. Used for building and deploying scalable training and serving pipelines.

Simple KFP Drumstick Catching Game

Standalone Kubeflow Pipelines (KFP 2.16.1) on a local kind cluster — tested on Apple Silicon (M3). Kustomize overlay, sample 3-step pipeline (preprocess → train → evaluate), and an ArgoCD Application for GitOps deployment.

mlopspl 🛠️🔄🚀 : E2E MLOps Vertex AI Pipelines # ML workflow # Kubeflow Pipelines SDK # Cloud Scheduler

KFP v2 pipeline fundamentals practiced locally — components, artifacts, control flow, and end-to-end ML pipeline. Foundation for Google Cloud Vertex AI Pipelines.

End-to-end customer churn prediction on Google Cloud Vertex AI Pipelines (KFP v2). XGBoost + SHAP, deterministic persona segmentation, daily snapshots, drift monitoring.