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KServe 0.7 Release


Dan Sun, Animesh Singh, Yuzhui Liu, Vedant Padwal on behalf of the KServe Working Group.

KFServing is now KServe and KServe 0.7 release is available, the release also ensures a smooth user migration experience from KFServing to KServe.

⚠ What's Changed?

  • InferenceService API group is changed from to #1826, the migration job is created for smooth transition.
  • Python SDK name is changed from kfserving to kserve.
  • KServe Installation manifests #1824.
  • Models-web-app is separated out of the kserve repository to models-web-app.
  • Docs and examples are moved to separate repository website.
  • KServe images are migrated to kserve docker hub account.
  • v1alpha2 API group is deprecated #1850.

🌈 What's New?

  • ModelMesh project is joining KServe under repository modelmesh-serving!

    ModelMesh is designed for high-scale, high-density and frequently-changing model use cases. ModelMesh intelligently loads and unloads AI models to and from memory to strike an intelligent trade-off between responsiveness to users and computational footprint. To learn more about ModelMesh features and components, check out the ModelMesh announcement blog and Join talk at #KubeCon NA to get a deeper dive into ModelMesh and KServe.

  • (Alpha feature) Raw Kubernetes deployment support, Istio/Knative dependency is now optional and please follow the guide to install and turn on RawDeployment mode.

  • KServe now has its own documentation website temporarily hosted on website.
  • Support v1 crd and webhook configuration for Kubernetes 1.22 #1837.
  • Triton model serving runtime now defaults to 21.09 version #1840.

🐞 What's Fixed?

  • Bug fix for Azure blob storage #1845.
  • Tar/Zip support for all storage options #1836.
  • Fix AWS_REGION env variable and add AWS_CA_BUNDLE for S3 #1780.
  • Torchserve custom package install fix #1619.

Join the community


We would like to thank everyone for their efforts on v0.7

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