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Kubeflow is an open-source platform for machine learning and MLOps on Kubernetes introduced by Google. The different stages in a typical machine learning lifecycle are represented with different software components in Kubeflow, including model development (Kubeflow Notebooks[4]), model training (Kubeflow Pipelines,[5] Kubeflow Training Operator[6]), model serving (KServe[a][7]), and automated machine learning (Katib[8]).

Each component of Kubeflow can be deployed separately, and it is not a requirement to deploy every component.[9]

History

The Kubeflow project was first announced at KubeCon + CloudNativeCon North America 2017 by Google engineers David Aronchick, Jeremy Lewi, and Vishnu Kannan[10] to address a perceived lack of flexible options for building production-ready machine learning systems.[11] The project has also stated it began as a way for Google to open-source how they ran TensorFlow internally.[12]

The first release of Kubeflow (Kubeflow 0.1) was announced at KubeCon + CloudNativeCon Europe 2018.[13][14] Kubeflow 1.0 was released in March 2020 via a public blog post announcing that many Kubeflow components were graduating to a “stable status”, indicating they were now ready for production usage.[15]

In October 2022, Google announced that the Kubeflow project had applied to join the Cloud Native Computing Foundation.[16][17] In July 2023, the foundation voted to accept Kubeflow as an incubating stage project.[18][19]

Components

Kubeflow Notebooks for model development

Machine learning models are developed in the notebooks component called Kubeflow Notebooks. The component runs web-based development environments inside a Kubernetes cluster, with native support for Jupyter Notebook, Visual Studio Code, and RStudio.[20]

Kubeflow Pipelines for model training

Once developed, models are trained in the Kubeflow Pipelines component. The component acts as a platform for building and deploying portable, scalable machine learning workflows based on Docker containers.[21] Google Cloud Platform has adopted the Kubeflow Pipelines DSL within its Vertex AI Pipelines product.[22]

Kubeflow Training Operator for model training

For certain machine learning models and libraries, the Kubeflow Training Operator component provides Kubernetes custom resources support. The component runs distributed or non-distributed TensorFlow, PyTorch, Apache MXNet, XGBoost, and MPI training jobs on Kubernetes.[6]

KServe for model serving

The KServe component (previously named KFServing[23]) provides Kubernetes custom resources for serving machine learning models on arbitrary frameworks including TensorFlow, XGBoost, scikit-learn, PyTorch, and ONNX.[24] KServe was developed collaboratively by Google, IBM, Bloomberg, NVIDIA, and Seldon.[23] Publicly disclosed adopters of KServe include Bloomberg,[25] Gojek,[26] the Wikimedia Foundation,[27] and others.[28]

Katib for automated machine learning

Lastly, Kubeflow includes a component for automated training and development of machine learning models, the Katib component. It is described as a Kubernetes-native project and features hyperparameter tuning, early stopping, and neural architecture search.[29]

Release timeline

Release timeline
Version Release date Release Information Release Blog
Kubeflow 0.1 5 April, 2018[2] – https://kubernetes.io/blog/2018/05/04/announcing-kubeflow-0.1/
Kubeflow 0.2 2 July, 2018[30] – https://medium.com/kubeflow/kubeflow-0-2-offers-new-components-and-simplified-setup-735e4c56988d
Kubeflow 0.3 5 October, 2018[31] – https://medium.com/kubeflow/kubeflow-0-3-simplifies-setup-improves-ml-development-98b8ca10bd69
Kubeflow 0.4 8 January, 2019[32] – https://medium.com/kubeflow/kubeflow-0-4-release-enhancements-for-machine-learning-productivity-d77c54df07a9
Kubeflow 0.5 9 April, 2019[33] – https://medium.com/kubeflow/kubeflow-v0-5-simplifies-model-development-with-enhanced-ui-and-fairing-library-78e19cdc9f50
Kubeflow 0.6 19 July, 2019[34] https://www.kubeflow.org/docs/releases/kubeflow-0.6/ https://medium.com/kubeflow/kubeflow-v0-6-a-robust-foundation-for-artifact-tracking-data-versioning-multi-user-support-9896d329412c
Kubeflow 0.7 17 October, 2019[35] https://www.kubeflow.org/docs/releases/kubeflow-0.7/ https://medium.com/kubeflow/kubeflow-v0-7-delivers-beta-functionality-in-the-leadup-to-v1-0-1e63036c07b8
Kubeflow 1.0 20 February, 2020[36] https://www.kubeflow.org/docs/releases/kubeflow-1.0/ https://blog.kubeflow.org/releases/2020/03/02/kubeflow-1-0-cloud-native-ml-for-everyone
Kubeflow 1.1 31 July, 2020[37] https://www.kubeflow.org/docs/releases/kubeflow-1.1/ https://blog.kubeflow.org/release/official/2020/07/31/kubeflow-1.1-blog-post
Kubeflow 1.2 18 November, 2020[38] https://www.kubeflow.org/docs/releases/kubeflow-1.2/ https://blog.kubeflow.org/release/official/2020/11/18/kubeflow-1.2-blog-post
Kubeflow 1.3 23 April, 2021[39] https://www.kubeflow.org/docs/releases/kubeflow-1.3/ https://blog.kubeflow.org/kubeflow-1.3-release/
Kubeflow 1.4 12 October, 2021[40] https://www.kubeflow.org/docs/releases/kubeflow-1.4/ https://blog.kubeflow.org/kubeflow-1.4-release/
Kubeflow 1.5 10 March, 2022[41] https://www.kubeflow.org/docs/releases/kubeflow-1.5/ https://blog.kubeflow.org/kubeflow-1.5-release/
Kubeflow 1.6 7 September, 2022[42] https://www.kubeflow.org/docs/releases/kubeflow-1.6/ https://blog.kubeflow.org/kubeflow-1.6-release/
Kubeflow 1.7 29 March, 2023[43] https://www.kubeflow.org/docs/releases/kubeflow-1.7/ https://blog.kubeflow.org/kubeflow-1.7-release/
Kubeflow 1.8 1 November, 2023[44] https://www.kubeflow.org/docs/releases/kubeflow-1.8/ https://blog.kubeflow.org/kubeflow-1.8-release/
Kubeflow 1.9 22 July, 2024[45] https://www.kubeflow.org/docs/releases/kubeflow-1.9/ https://blog.kubeflow.org/kubeflow-1.9-release/
Kubeflow 1.10 1 April, 2025[3] https://www.kubeflow.org/docs/releases/kubeflow-1.10/ https://blog.kubeflow.org/kubeflow-1.10-release/

Notes

  1. ^ KServe was previously known as KFServing[23]

References

  1. ^ “Kubeflow Website – Working Groups”.
  2. ^ a b “Kubeflow 0.1 – Release Tag”. GitHub.
  3. ^ a b “Kubeflow 1.10 – Release Information”.
  4. ^ “Kubeflow Website – Kubeflow Notebooks”.
  5. ^ “Kubeflow Website – Kubeflow Pipelines”.
  6. ^ a b “Kubeflow GitHub – Kubeflow Training Operator”. GitHub.
  7. ^ “Kubeflow Website – KServe”.
  8. ^ “Kubeflow Website – Katib”.
  9. ^ “Kubeflow Website – Installing Kubeflow”.
  10. ^ ““Hot Dogs or Not” – At Scale with Kubernetes [I] – Vish Kannan & David Aronchick, Google”. YouTube. 15 December 2017.
  11. ^ “Introducing Kubeflow – A Composable, Portable, Scalable ML Stack Built for Kubernetes”. 21 December 2017.
  12. ^ “Kubeflow Website – History”.
  13. ^ “Google-led Kubeflow, machine learning for Kubernetes, begins to take shape”. 4 May 2018.
  14. ^ “Announcing Kubeflow 0.1”. 4 May 2018.
  15. ^ “Kubeflow 1.0: Cloud-Native ML for Everyone”. 2 March 2020.
  16. ^ Lamkin, Thea (2022-10-24). “Kubeflow has applied to become a CNCF incubating project”. Kubeflow. Retrieved 2023-11-02.
  17. ^ “Kubeflow applies to become a CNCF incubating project”. Google Open Source Blog. 2022-10-24. Retrieved 2023-11-02.
  18. ^ “Kubeflow brings MLOps to the CNCF Incubator”. Cloud Native Computing Foundation. 2023-07-25. Retrieved 2023-11-02.
  19. ^ “Kubeflow joins the CNCF family”. Google Open Source Blog. 2023-07-25. Retrieved 2023-11-02.
  20. ^ “Kubeflow Website – Kubeflow Notebooks Overview”.
  21. ^ “Kubeflow Website – Kubeflow Pipelines Introduction”.
  22. ^ “Vertex AI – Building a pipeline”.
  23. ^ a b c “KServe: The next generation of KFServing”. 27 September 2021.
  24. ^ “KServe GitHub”. GitHub.
  25. ^ “The journey to build Bloomberg’s ML Inference Platform Using KServe (formerly KFServing)”. Bloomberg L.p. 12 October 2021.
  26. ^ “Merlin: Making ML Model Deployments Magical”.
  27. ^ “Machine Learning/LiftWing”.
  28. ^ “KServe Website – Adopters of KServe”.
  29. ^ “Kubeflow GitHub – Katib”. GitHub.
  30. ^ “Kubeflow 0.2 – Release Tag”. GitHub.
  31. ^ “Kubeflow 0.3 – Release Tag”. GitHub.
  32. ^ “Kubeflow 0.4 – Release Tag”. GitHub.
  33. ^ “Kubeflow 0.5 – Release Tag”. GitHub.
  34. ^ “Kubeflow 0.6 – Release Information”.
  35. ^ “Kubeflow 0.7 – Release Information”.
  36. ^ “Kubeflow 1.0 – Release Information”.
  37. ^ “Kubeflow 1.1 – Release Information”.
  38. ^ “Kubeflow 1.2 – Release Information”.
  39. ^ “Kubeflow 1.3 – Release Information”.
  40. ^ “Kubeflow 1.4 – Release Information”.
  41. ^ “Kubeflow 1.5 – Release Information”.
  42. ^ “Kubeflow 1.6 – Release Information”.
  43. ^ “Kubeflow 1.7 – Release Information”.
  44. ^ “Kubeflow 1.8 – Release Information”.
  45. ^ “Kubeflow 1.9 – Release Information”.