Kubeflow
by Community
Machine Learning Toolkit for Kubernetes
OSS
Kubeflow
Added 1 June 2026
Overview
Kubeflow is an open-source ML toolkit that runs on Kubernetes, providing components for building and deploying machine learning workflows. It abstracts Kubernetes complexity to let teams define, train, and serve models as containerized pipelines without managing infrastructure directly.
Best for
Best for
Teams with Kubernetes infrastructure who need to standardize ML workflows across on-prem or multi-cloud environments
Use cases
- Orchestrating multi-step training pipelines across distributed clusters
- Managing model serving and inference at scale on Kubernetes
- Automating hyperparameter tuning and experiment tracking workflows
Notes
Kubeflow is an open-source ML toolkit that runs on Kubernetes, providing components for building and deploying machine learning workflows. It abstracts Kubernetes complexity to let teams define, train, and serve models as containerized pipelines without managing infrastructure directly.
15,700 stars on GitHub. Last updated 2026-05-24. Licensed Apache-2.0.
Use cases
- Orchestrating multi-step training pipelines across distributed clusters
- Managing model serving and inference at scale on Kubernetes
- Automating hyperparameter tuning and experiment tracking workflows
Pros
- Runs on any Kubernetes cluster, avoiding vendor lock-in
- Handles distributed training and serving natively
- Active community with broad ecosystem integration
Cons
- Requires existing Kubernetes expertise to operate effectively
- Steep learning curve for teams new to container orchestration
- Observability tooling is basic compared to managed ML platforms
Indexed from awesome-llmops and enriched against its public facts.
Pros
- Runs on any Kubernetes cluster, avoiding vendor lock-in
- Handles distributed training and serving natively
- Active community with broad ecosystem integration
Cons
- Requires existing Kubernetes expertise to operate effectively
- Steep learning curve for teams new to container orchestration
- Observability tooling is basic compared to managed ML platforms
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
Airflow
Community
Platform created by the community to programmatically author, schedule and monitor workflows.
ClearML
Community
ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
Flyte
Community
Dynamic, resilient AI orchestration. Coordinate data, models, and compute as you build AI workflows.
KubeAI
Community
AI Inference Operator for Kubernetes. The easiest way to serve ML models in production. Supports VLMs, LLMs, embeddings, and speech-to-text.
Metaflow
Community
Build, Manage and Deploy AI/ML Systems
MLRun
Community
MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environ
PAI
Community
Resource scheduling and cluster management for AI
Polyaxon
Community
Open Source AI Infra & Engineering Control Plane
Prefect
Community
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
Starwhale
Community
an MLOps/LLMOps platform
VDP
Community
🔮 Instill Core is a full-stack AI infrastructure tool for data, model and pipeline orchestration, designed to streamline every aspect of building versatile AI-first applications
ZenML
Community
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
TensorFlow
Community
An Open Source Machine Learning Framework for Everyone
PyTorch
Community
Tensors and Dynamic neural networks in Python with strong GPU acceleration
scikit-learn
Community
scikit-learn: machine learning in Python
Awesome Production Machine Learning
Community
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Delta-Lake
Community
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Determined
Community
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch
Feast
Community
The Open Source Feature Store for AI/ML
Featureform
Community
The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
Great Expectations
Community
Always know what to expect from your data.
Hopsworks
Community
Hopsworks - Data-Intensive AI platform with a Feature Store
Kaito
Community
Kubernetes AI Toolchain Operator
Katib
Community
Automated Machine Learning on Kubernetes
Kserve
Community
Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes
Kueue
Community
Kubernetes-native Job Queueing
LakeFS
Community
lakeFS - Data version control for your data lake | Git for data
ModelDB
Community
Open Source ML Model Versioning, Metadata, and Experiment Management
Primehub
Community
open-source MLOps platform
Seldon-core
Community
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
TFServing
Community
A flexible, high-performance serving system for machine learning models
Volcano
Community
A Cloud Native Batch System (Project under CNCF)
Weco Observe
Community
Build and Optimize your machine learning pipeline with the Weco Platform - based on AIDE ML, the LLM-powered code optimization Agent for Machine Learning Engineering.
Get the free Developer’s Field Guide
A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.
Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.