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Announcing KServe v0.7 - Smooth Transition from KFServing to KServe

· 4 min read
Dan Sun
Dan Sun
Co-Founder, KServe
Animesh Singh
Animesh Singh
KServe Contributor
Yuzhui Liu
Yuzhui Liu
KServe Contributor
Vedant Padwal
Vedant Padwal
KServe Contributor

Published on October 11, 2021

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 serving.kubeflow.org to serving.kserve.io #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.

🔍 Release Notes​

For complete release notes including all changes, bug fixes, and known issues, visit the GitHub release page.

🙏 Acknowledgments​

We want to thank all the contributors who made this release possible:

Individual Contributors:

Core Contributors: The KServe maintainers and working group members

Community: Everyone who reported issues, provided feedback, and tested features during this important transition

🤝 Join the Community​

Happy serving!

The KServe team is committed to making machine learning model serving simple, scalable, and standardized. Thank you for being part of our community during this important transition!