Kubeflow is an

open-source Open source is source code that is made freely available for possible modification and redistribution. Products include permission to use the source code, design documents, or content of the product. The open-source model is a decentralized sof ...

platform for

machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...

and

MLOps MLOps or ML Ops is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently. The word is a compound of "machine learning" and the continuous development practice of DevOps in the software fi ...

Kubernetes Kubernetes (, commonly stylized as K8s) is an open-source container orchestration system for automating software deployment, scaling, and management. Google originally designed Kubernetes, but the Cloud Native Computing Foundation now maintains ...

introduced by

Google Google LLC () is an American multinational technology company focusing on search engine technology, online advertising, cloud computing, computer software, quantum computing, e-commerce, artificial intelligence, and consumer electronics. ...

. The different stages in a typical machine learning lifecycle are represented with different

software components Component-based software engineering (CBSE), also called component-based development (CBD), is a branch of software engineering that emphasizes the separation of concerns with respect to the wide-ranging functionality available throughout a give ...

in Kubeflow, including model development ''( Kubeflow Notebooks)'', model training ''( Kubeflow Pipelines'',''

Kubeflow Training Operator 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 ...

)'', model serving ''( KServe)'', and automated machine learning ''(

Katib A katib ( ar, كَاتِب, ''kātib'') is a writer, scribe, or secretary in the Arabic-speaking world, Persian World, and other Islamic areas as far as India. In North Africa, the local pronunciation of the term also causes it to be written ketib ...

)''. Each component of Kubeflow can be deployed separately, and it is not a requirement to deploy every component.

History

The Kubeflow project was first announced at '' KubeCon + CloudNativeCon North America 2017'' by

engineers David Aronchick, Jeremy Lewi, and Vishnu Kannan to address a perceived lack of flexible options for building production-ready machine learning systems. The project has also stated it began as a way for Google to open-source how they ran

TensorFlow TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. "It is machine learning ...

internally. The first release of Kubeflow (Kubeflow 0.1) was announced at ''KubeCon + CloudNativeCon Europe 2018'' with claims of having already become among the top 2% of

GitHub GitHub, Inc. () is an Internet hosting service for software development and version control using Git. It provides the distributed version control of Git plus access control, bug tracking, software feature requests, task management, continuous ...

projects ever. 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.

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 Project Jupyter () is a project with goals to develop open-source software, open standards, and services for interactive computing across multiple programming languages. It was spun off from IPython in 2014 by Fernando Pérez and Brian Granger ...

Visual Studio Code Visual Studio Code, also commonly referred to as VS Code, is a source-code editor made by Microsoft with the Electron Framework, for Windows, Linux and macOS. Features include support for debugging, syntax highlighting, intelligent code complet ...

, and

RStudio RStudio is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server ...

''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 Portable may refer to: General * Portable building, a manufactured structure that is built off site and moved in upon completion of site and utility work * Portable classroom, a temporary building installed on the grounds of a school to provide a ...

, scalable machine learning workflows based on Docker containers.

Google Cloud Platform Google Cloud Platform (GCP), offered by Google, is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search, Gmail, Google Drive, and YouTube. Alongside ...

has adopted the ''Kubeflow Pipelines DSL'' within its ''Vertex AI Pipelines'' product.

''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

PyTorch PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella. It is free and open ...

, Apache MXNet, XGBoost, and

MPI MPI or Mpi may refer to: Science and technology Biology and medicine * Magnetic particle imaging, an emerging non-invasive tomographic technique * Myocardial perfusion imaging, a nuclear medicine procedure that illustrates the function of the hear ...

training jobs on Kubernetes.

''KServe'' for model serving

The ''KServe'' component (previously named KFServing) provides Kubernetes custom resources for serving machine learning models on arbitrary frameworks including

, XGBoost,

scikit-learn scikit-learn (formerly scikits.learn and also known as sklearn) is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support-vector m ...

, and

ONNX The Open Neural Network Exchange (ONNX) [] is an Open-source software, open-source artificial intelligence ecosystem of technology companies and research organizations that establish open standards for representing machine learning algorithms and ...

. KServe was developed collaboratively by

, IBM, Bloomberg,

NVIDIA Nvidia CorporationOfficially written as NVIDIA and stylized in its logo as VIDIA with the lowercase "n" the same height as the uppercase "VIDIA"; formerly stylized as VIDIA with a large italicized lowercase "n" on products from the mid 1990s to ...

, and Seldon. Publicly disclosed adopters of KServe include Bloomberg,

Gojek PT Gojek Indonesia (stylized in all lower case and stylized ''j'' as goȷek, formerly styled as GO-JEK) is an Indonesian on-demand multi-service platform and digital payment technology group based in Jakarta. Gojek was first established in Indo ...

, and others.

''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 In machine learning, early stopping is a form of regularization used to avoid overfitting when training a learner with an iterative method, such as gradient descent. Such methods update the learner so as to make it better fit the training data with ...

, and

neural architecture search Neural architecture search (NAS) is a technique for automating the design of artificial neural networks (ANN), a widely used model in the field of machine learning. NAS has been used to design networks that are on par or outperform hand-designed a ...

Release timeline

Notes

References

External links

* * {{Google FOSS 2018 software Cloud infrastructure Data mining and machine learning software Software using the Apache license Free software programmed in Python Free software programmed in Go