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awesome-kubeflow
A curated list of awesome projects and resources related to Kubeflow (a CNCF incubating project)
https://github.com/terrytangyuan/awesome-kubeflow
- Kubeflow Main Repository - end to access major components of Kubeflow.
- Katib - native project for automated machine learning (AutoML).
- Pipelines
- Training Operator - distributed TensorFlow/PyTorch/Apache MXNet/XGBoost/MPI jobs on Kubernetes.
- Arena
- Argo Workflows - native workflow engine for orchestrating parallel jobs on Kubernetes.
- Couler
- deployKF
- Kale
- Kedro - source Python framework for creating reproducible, maintainable and modular data science code.
- KServe
- MLRun
- ModelDB - source system to version machine learning models including their ingredients code, data, config, and environment and to track ML metadata across the model lifecycle.
- Polyaxon
- Seldon
- SQLFlow
- ZenML - ready MLOps pipelines.
- Elyra - centric extensions to JupyterLab Notebooks, that contains a visual pipeline editor.
- Pipeline Editor - pipelines.pipeline-editor-vscode).
- WizStudio
- Continuous Machine Learning with Kubeflow
- Distributed Machine Learning Patterns - world scenarios and hands-on projects.
- Kubeflow for Machine Learning: From Lab to Production - grade machine learning implementations with Kubeflow and shows data engineers how to make models scalable and reliable.
- Kubeflow in Action: End-to-End Machine Learning - on guide to deploying machine learning to production using the Kubeflow MLOps platform.
- Kubeflow Operations Guide: Managing Cloud and On-Premise Deployment
- official Kubeflow Project blog
- Data Science Meets Devops: MLOps with Jupyter, Git, & Kubernetes
- Elastic Training with MPI Operator and Practice
- Enabling Kubeflow with Enterprise-Grade Auth for On-Premise Deployments
- GitOps for Kubeflow using Argo CD
- Hardening Kubeflow Security for Enterprise Environments
- Humans of Cloud Native: From Argo to Mentoring and Everything In Between
- Introduction to Kubeflow MPI Operator and Industry Adoption
- KServe: The Next Generation of KFServing
- Kubeflow & Kale Simplify Building Better ML Pipelines With Automatic Hyperparameter Tuning
- Kubeflow’s 1.4 Release Lays the Foundation for Advanced ML Metadata Workflows
- Kubeflow 1.0 - Cloud Native ML for Everyone
- Kubeflow 1.1 Improves ML Workflow Productivity, Isolation & Security, and GitOps
- Kubeflow Continues to Move into Production
- Kubeflow Has Applied To Become a CNCF Incubating Project
- Kubeflow Katib: Scalable, Portable and Cloud Native System for AutoML
- Kubeflow v1.5 Improves ML Model Accuracy, Reduces Infrastructure Costs and Optimizes MLOps
- Kubeflow v1.6 Delivers Support for Kubernetes v1.22 and Introduces an Alpha Release of the Kubeflow Pipeline v2 Functionality
- Kubeflow Welcomes Two Google Summer of Code Students
- Kubeflow’s 2nd Doc Sprint: 10+ New Docs & Samples Ahead of Kubeflow 1.0
- Kubeflow is More Accessible than Ever
- Operationalize, Scale and Infuse Trust in AI Models using KFServing
- Record Metadata on Kubeflow from Notebooks
- Running Kubeflow at Intuit: Enmeshed in the Service Mesh
- Scalable and Cloud-Native Hyperparameter Tuning System
- The Kubeflow 1.3 Release Streamlines ML Workflows and Simplifies ML Platform Operations
- Unified Training Operator Release Announcement
- official Kubeflow YouTube channel
- Kubeflow Summit Europe 2024
- Kubeflow Summit 2023
- Community Meeting Recordings
- A 10 Minute Introduction to Kubeflow: Basics, Architecture & Components
- Accelerate ML Model Development for Autonomous Vehicles in Aurora
- Accelerating Machine Learning App Development with Kubeflow Pipelines
- A Simple, NVIDIA-accelerated Kubeflow Pipeline
- A Tour of Katib's new UI for Kubeflow 1.3
- AutoML and Training WG Summit 2021
- Bridging into Python Ecosystem with Cloud-Native Distributed Machine Learning Pipelines
- Building a Machine Learning Pipeline with Kubeflow
- Building and Managing a Centralized Kubeflow Platform at Spotify
- Building an ML Application Platform from the Ground Up
- Building AutoML Pipelines With Argo Workflows and Katib
- Building end-to-end ML workflows with Kubeflow Pipelines
- Building Real Time Image Classification with Kubeflow Orchestrator
- Building Together: Community in Kubeflow
- Charmed for Kubeflow: A Distribution for Everybody
- Cloud Native AutoML with Argo Workflows and Katib
- Converting Kaggle Competitions into Kubeflow Pipelines
- DGL Operator and Graph Training
- Distributed Training and HPO Deep Dive
- Enterprise MLOps using Kubeflow with DKube
- Experiment Tracking with Kubeflow
- Feast: Feature Storage for Machine Learning
- From Notebook to Kubeflow Pipelines to KFServing: the Data Science Odyssey
- From Notebook to Kubeflow Pipelines with HP Tuning
- From Notebook to Kubeflow Pipelines with MiniKF & Kale
- From Zero to Kubeflow
- Hiding Kubernetes Complexity for ML Engineers Using Kubeflow
- Hyperparameter Tuning Using Kubeflow
- Hyperparameter Tuning with Katib
- Introducing Couler: Unified Interface for Constructing and Managing Workflows
- Katib and Training Operator
- Katib User Journey
- KFServing: Enabling Serverless Workloads Across Model Frameworks
- KServe: The State and Future of Cloud Native Model Serving
- Kubeflow & Alibaba Arena
- Kubeflow & TFX
- Kubeflow 101 from Google Cloud
- Kubeflow: Machine Learning on Kubernetes
- Kubeflow and the ML Landscape
- Kubeflow Experiments at LinkedIn
- Kubeflow Fairing
- Kubeflow for Enterprise – Samsung Case
- Kubeflow inference on knative
- Kubeflow Katib & Hyperparameter Tuning
- Kubeflow Pipelines 2.0: Introduction & Roadmap
- Kubeflow Universal Training Operator
- Kubeflow vs SageMaker in Machine Learning
- Machine Learning as Code: GitOps for ML with Kubeflow and ArgoCD
- Managing Thousands of Automatic Machine Learning Experiments with Argo and Katib
- MiniKF: The Fastest and Easiest Way to a Local Kubeflow
- MLOps and AutoML in Cloud-Native Way with Kubeflow and Katib
- ModelDB: Open-source Model Management
- Model Monitoring for Model Trained and Served on Kubeflow
- Multi-user Kubeflow Environments
- Nested Workflows in Kubeflow Pipelines
- Neural Architecture Search System on Kubeflow
- New UI for Kubeflow components
- Orchestrating Apache Spark with Kubeflow on Kubernetes
- Paddle Operator and EDL Introduction
- Production-Ready AI Platform on Kubernetes
- Roblox User Story
- Serverless Magic for ML Orchestration using Kubeflow
- Taming Your AI/ML Workloads with Kubeflow
- Tour of New Katib UI
- Towards Cloud-Native Distributed Machine Learning Pipelines at Scale
- Training and Serving ML Model using Kubeflow
- Understanding the Earth: Machine Learning with Kubeflow Pipelines
- Using Pipelines in Katib
- When Machine Learning Toolkit for Kubernetes Meets PaddlePaddle
- Community Calendar
- Working Groups
- GitHub Organization
- Community Governance
- 2023 - user-survey-2022/), [2019 Fall](https://medium.com/kubeflow/kubeflow-community-user-survey-fall-2019-a84776c71743), [2019 Spring](https://medium.com/kubeflow/kubeflow-community-user-survey-spring-2019-44f86c794e67))
- Slack
Keywords
machine-learning
18
kubernetes
13
kubeflow
11
mlops
11
tensorflow
8
data-science
5
kubeflow-pipelines
5
pytorch
5
python
5
pipelines
5
ai
5
workflow
4
deep-learning
4
argo-workflows
3
k8s
3
llm
3
ml
3
artificial-intelligence
3
cloud-native
3
argo
2
airflow
2
docker
2
data-engineering
2
gitops
2
jupyterlab
2
knative
2
workflow-engine
2
jupyter
2
notebook
2
automl
2
huggingface
2
jax
2
pipeline
2
model-serving
2
xgboost
2
apache-airflow
2
scheduler
1
distributed-computing
1
workflow-automation
1
workflow-management
1
tekton-pipelines
1
argocd
1
unified-interface
1
unified-api
1
jupyter-notebook
1
dag
1
cncf
1
batch-processing
1
gpu
1
fine-tuning
1