Resource Management Working Group: Participants, Outcomes, and Priorities

4th chunk of `content/en/blog/_posts/2017-09-00-Introducing-Resource-Management-Working.md`

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 Folks from Intel, NVIDIA, Google, IBM, Red Hat. and Microsoft (among others) participated.&nbsp;  
You can read the outcomes of that 3-day meeting [here](https://docs.google.com/document/d/13_nk75eItkpbgZOt62In3jj0YuPbGPC_NnvSCHpgvUM/edit).  

 The group’s prioritized list of features for increasing workload coverage on Kubernetes enumerated in the [charter](https://github.com/kubernetes/community/tree/master/wg-resource-management) of the Resource Management Working group includes:   

- Support for performance sensitive workloads (exclusive cores, cpu pinning strategies, NUMA)
- Integrating new hardware devices (GPUs, FPGAs, Infiniband, etc.)
- Improving resource isolation (local storage, hugepages, caches, etc.)
- Improving Quality of Service (performance SLOs)
- Performance benchmarking
- APIs and extensions related to the features mentioned above
The discussions made it clear that there was tremendous overlap between needs for various workloads, and that we ought to de-duplicate requirements, and plumb generically.

Title: Resource Management Working Group: Participants, Outcomes, and Priorities

Summary

The Resource Management Working Group's kickoff meeting included participants from Intel, NVIDIA, Google, IBM, Red Hat, and Microsoft. The outcomes of the meeting are documented in a linked document. The group's priorities, outlined in their charter, include supporting performance-sensitive workloads, integrating new hardware devices, improving resource isolation and quality of service, performance benchmarking, and related APIs and extensions.