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  • Name of proposed project: KServe

  • Requested project maturity level [Graduation or Incubation]: Incubation

  • Project description [what it does, why it is valuable, origin and history, ongoing development]:

    KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and Canary Rollouts to your ML deployments. It enables a simple, pluggable, and complete story for Production ML Serving including prediction, pre-processing, post-processing and explainability.

  • Statement on alignment with LF AI’s mission:

    KServe is built to offer a standard managed inference services that could help unify the model deployment process across ML frameworks, shorten the time-to-market for serving ML models in production at scale and reduce the complexity of implementation. KServe can be a great addition for the complete soultion for the end to end ML lifecycle and integrated with feature store, trusted AI projects under LF umbrella.

  • Describe identified possible collaboration opportunities with current LF AI hosted projects:

    • Feast
    • AI Explainability 360
    • AI Fairness 360
    • Adversarial Robustness Toolbox (ART)

  • License name, version, and URL to the license text:

    Apache 2.0 https://github.com/kserve/kserve/blob/master/LICENSE

  • URL to location of source code (GitHub, etc.):

    https://github.com/kserve

  • Please list tools in use by the project:

  • Issue tracker (GitHub, JIRA, etc) - Please confirm tools in use.

  • Collaboration tools (mailing lists, wiki, IRC, Slack, Glitter, etc.) - Please confirm tools in use:

  • External dependencies including licenses (name and version) of those dependencies.

    Major External Dependencies:

    • Knative (Apache-2)
    • Istio (Apache-2)
    • Seldon MLServer/Alibi (Apache-2)
    • Triton Inference Server (BSD)

    The individual packages in use by the project can be found in the following locations:

  • Initial committers (name, email, organization) and how long have they been working on project?

    • Dan Sun @yuzisun Bloomberg(30 months+)
    • Animesh Singh @animeshsingh IBM(30 months+)
    • Clive Cox @cliveseldon Seldon(30 months+)
    • David Goodwin @deadeyegoodwin NVIDIA(30 months+)
    • Yuzhui Liu @yuzliu Bloomberg(30 months+)
    • Tommy Li @Tomcli IBM(30 months+)
    • Theofilos Papapanagiotou @theofpa Prosus(18 months+)
    • Qianshan Chen @iamlovingit Inspur(18 months+)
    • Nick Hill @njhill IBM(12 months+)
    • Paul Van Eck @pvaneck IBM(12 months+)
    • Jagadeesh J @jagadeeshi2i Ideas2IT(12 months+)

  • Have the project defined the roles of contributor, committer, maintainer, etc.? Please document it in MAINTAINERS.md.

    We have defined the approvers and reviewers in https://github.com/kserve/kserve/blob/master/OWNERS

  • Total number of contributors to the project including their affiliations at the time of submitting this proposal:

    Total 137 contributors from https://github.com/kserve/kserve/graphs/contributors

  • Does the project have a release methodology? Please document it in RELEASES.md.

  • Does the project have a code of conduct? If yes, please share the URL. If no, please created CODE_OF_CONDUCT.md and point to https://lfprojects.org/policies/code-of-conduct/. You can use [email protected] as email for contact on this topic.

    The code of conduct will be linked to https://www.linuxfoundation.org/code-of-conduct/

  • Do you have any specific infrastructure requests needed as part of hosting the project in the LF AI?

    AWS is currently providing infrastructure for running our e2e tests, but the budget is going to expire soon so we'd like move to a new cloud account to run e2e tests.

  • Project website - Do you have a web site? If no, did you reserve a domain, and would like you to have a website created?

    Currently we are hosting the website on github pages https://kserve.github.io/website, but we have reserved the domain kserve.io.

  • Project governance - Do you have a working governance model for the project? Please provide URL to where it is documented, typically GOVERNANCE.md.

  • Social media accounts - Do you have any Twitter/LinkedIn/Facebook/etc. project accounts? Please provide pointers. Not yet.

  • Existing sponsorship (e.g., whether any organization has provided funding or other support to date, and a description of that support), if any.

    This project was originally incubated under Kubeflow, now it is moved to an independent github organization maintained by Bloomberg, IBM and community contributors.