kubeflow/kubeflow
The Cloud Native AI Platform observed · 2026-10-20
Health v2 · maintenance only
78/100
- Activity 97
- Release rhythm 42
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.
- gap_med: 275.5
- age_days: 3246
- days_rel: 174
- days_push: 20
- n_releases_24m: 3
Adoption not part of the score
15915 stars · 2704 forks observed · 2026-10-20
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Kubeflow is a CNCF-graduated, Kubernetes-native toolkit for building AI/ML platforms, comprising subprojects like Pipelines, Notebooks, Trainer, Katib, Hub, and a Spark Operator. This repository is the gateway to those subprojects and shared metadata, with development happening in individual subproject repos.
Use cases
- run machine learning pipelines on kubernetes
- fine-tune llms on a kubernetes cluster
- run jupyter notebooks in kubernetes
- hyperparameter tuning and automl on k8s
- orchestrate distributed model training with pytorch
- build an end-to-end mlops platform
- deploy rag and genai workflows at scale
- manage model versions and registry metadata
When to choose
- you already run Kubernetes and want a modular, composable AI platform on top of it
- you need scalable distributed training, pipelines, notebooks, and hyperparameter search in one ecosystem
- you want a CNCF-graduated, vendor-neutral foundation to build a custom AI platform
- you need GenAI lifecycle tooling from synthetic data to inference and evaluation
When to avoid
- you have no Kubernetes cluster or want a simple single-node ML setup
- you need a lightweight all-in-one ML tool without significant operational overhead
- you only need one small capability and don't want to deploy a full distribution
- your team lacks Kubernetes administration experience
Facets
framework · maturity stable
machine-learning llm-training workflow-automation scheduling container-orchestration developer-tools machine-learning deep-learning large-language-models data-science cloud-computing cloud self-hosted python go mlops kubeflow pipelines notebooks hyperparameter-tuning distributed-training automl cncf genai model-registry containers devops kubernetes docker
10 sources
- readme: https://github.com/kubeflow/kubeflow · fetched 2026-10-20 · 3e37f216f636
- homepage: https://www.kubeflow.org/ · fetched 2026-10-19 · 89565dda601c
- site_page: https://www.kubeflow.org/docs · fetched 2026-10-19 · 2d48c8aa19c2
- site_page: https://www.kubeflow.org/docs/about/community · fetched 2026-10-19 · 85bbf5395b12
- site_page: https://www.kubeflow.org/docs/started · fetched 2026-10-19 · 52d4becf41e9
- site_page: https://www.kubeflow.org/docs/about/contributing · fetched 2026-10-19 · 53b2f217c21b
- site_page: https://www.kubeflow.org/docs/genai/use-cases · fetched 2026-10-19 · bfca00da3bad
- site_page: https://www.kubeflow.org/docs/started/architecture · fetched 2026-10-19 · eeb497b45570
- site_page: https://www.kubeflow.org/docs/started/installing-kubeflow · fetched 2026-08-29 · a977fcac93bf
- site_page: https://www.kubeflow.org/docs/components/notebooks/overview · fetched 2026-10-19 · 435150cc5c5d
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| kubeflow/kubeflow | main | 78 |
For agents
markdown · JSON · MCP: product_card(name="kubeflow/kubeflow")
Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem