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Home / Intel in Cloud Native / Community

Community

Through leadership that spans code contributions, board membership, participation in special interest groups (SIGs) and work groups, and event sponsorship, Intel helps ensure continued growth and vitality of the Kubernetes community.

Code Contributions

Our early contributions to Kubernetes helped extend capabilities and close critical gaps. We helped shape the architecture and requirements for device plugins, enabled greater CPU management through CPU pinning and node feature discovery, and introduced new networking features, such as multiple network interfaces and single root I/O virtualization.

 

Today, we’re continuing to advance Kubernetes, and ensure that businesses can take full advantage of high-performing Intel® technologies. An example is the support of Intel® Cache Allocation Technology (Intel® CAT) through Kubernetes, which Intel submitted to the community for review. Performance benchmarks show that it can significantly benefit a high priority workload by enhancing cache performance.

Proposal

Code

SIG OpenStack

Position: Lead

This group coordinates the cross-community efforts of the OpenStack and Kubernetes communities, including OpenStack-related contributions to Kubernetes projects. Committed to enabling innovation through open cloud technologies, Intel works across both communities.

 
SIG Node

Position: Owner, Node Feature Discovery subproject

Intel is actively involved in the SIG Node, leading the Node Feature Discovery subproject. We are helping users identify key features available on nodes through our work in node labeling. Our participation in this SIG began with a PR for Opaque Integer Resources in the Kubernetes 1.5 release, and has continued with contributions to Extended Resources and the Node Feature Discovery feature set.

Kubelet CPU Manager Project

Position: Author & Approver

Intel plays an active role as both an author and approver within the Kubelet CPU Manager project. We authored an initial proposal for the CPU Manager, as well as the NUMA Topology Manager.

Device Plugins

Position: Architect & Author

Intel was involved in bringing this topic to the community, from the early design phases through prototypes and reviews. We are also actively involved in ongoing maintenance and discussions around future enhancements.

WG Machine Learning

Position: Chairs

The aim of this working group is to identify and fix gaps in Kubernetes to better support machine learning applications.

SIG Cluster Lifecycle

Position: Reviewers, kubeadm subproject

Intel actively participates in the SIG Cluster Lifecycle, aimed to improve the user experience in deploying and upgrading minimum viable Kubernetes clusters that conform to best practices. We serve as reviewers within the kubeadm subproject, the primary deployment tool, building block and set of APIs for other deployment tools, including Cluster API. Our contributions have included design, implementation, refactoring and bug fixes in the following areas:

  • Automatic version selection, including ability to deploy custom and CI builds

  • Bootstrapping clusters in enterprise networks with restricted Internet connectivity

  • Bootstrapping clusters in air-gapped environments

  • Support for alternative container runtimes (CRI-O, containerd,...)

  • Clear Linux specific fixes

SIG Testing

Position: Approvers, E2E Node

Through our work with the Persistent Memory Container Storage Interface driver, Intel has contributed to the overall Node E2E test suite.

 
SIG Kubernetes CSI

Position: Approver, CSI Testing

Through our work with the Persistent Memory Container Storage Interface (PMEM-CSI) driver, Intel has contributed to the CSI testing project, helping enhance the CSI release process, and supported a number of documentation deliverables. Current work underway includes Jaeger tracing support.