KFServing is a project created initially by Google, Bloomberg, IBM, NVidia, Seldon under Kubeflow in 2019. It aims to provide a standard production grade model serving solution on Kubernetes. After publishing the open source project, we have seen an explosion in demand for the software, leading to strong adoption and community growth. The scope of the project has changed since, we have also developed sub components like ModelMesh, Model Web App which now demands its own github organization. The KFServing WG members decide to move KFServing development code out of Kubeflow GitHub organization to its independent organization https://github.com/kserve for the project graduation under the stewardship of Kubeflow Serving Working Group leads.
The project is renamed to KServe from KFServing to retain the connection and brand recognition.
The API group is changed from serving.kubeflow.org to serving.kserve.io.
- Issue 1826: Go module and API group change
- Regenerate
InferenceService,TrainedModelCRD with the new API group - Regenerate OpenAPI spec and
swagger.json
The Python SDK pypi package is renamed to kserve from kfserving, see Issue 1827.
- Regenerate python SDK from swagger.json
- Update SDK API with the new package name
kserve - Update model servers to import the new package
kserve - Update SDK docs
The KServe control plane is installed in kserve namespace instead of kfserving-system, see Issue 1824.
- Update API group for the webhook configurations
- Update Standalone/Kubeflow installation manifests overlays
- Update quick install script
- Update
Makefileand image patch scripts
Prow is designed for using plugins like /lgtm /approve and integration with github repo members makes it easy to manage all the projects in a fine-grained way,
though these can be implemented using individual github plugins. KServe has setup own Prow cluster installed with Tide for the github review and approval process using the
KServe OSS Bot.
For now we reuse the current kubeflow AWS e2e testing infra in the kserve github organization by adding the configuration to submit the presubmit job to KServe Github Repository.
- Update e2e presubmit job to use AWS e2e test Bot
- Update e2e test scripts with new SDK package
kserve
All the new images released from KServe should be published to the kserve docker hub organization.
- Migrate all existing images from gcr.io to docker hub
- Update github workflow to use the dockerhub account
kserve
We plan to integrate KServe 0.7 in Kubeflow 1.5 release.
- Create a new
KServecomponent forKubeflow Pipeline, see issue 1829 - Add KServe component to Kubeflow conformance test
Separate out models web-app to its own repository and setup CI/CD, see issue 1820.
- Test out the models UI after the name change
All the existing documentation and examples are moving to kserve/website which is built with mkdocs and the website is hosted on netlify.
- Update main concept, architecture diagrams
- Update administration guide
- Update core inference examples
- Update storage examples
- Update explanation examples
- Update logger and monitoring examples
- Update drift detect and outlier examples
- Update notebook examples
- Update community and contribution guidelines
For users that are migrating from kfserving, kserve installs in its own namespace kserve.
The migration script scales down the kfserving controller in the cluster, it then converts the InferenceService CR from kubeflow.org to kserve.io, and reconciled in the kserve controller.
The migration should not impact the running InferenceServices.
The previous KFServing 0.5.x and KFServing 0.6.x released are still supported in six months time frame after KServe 0.7 is released.