Presentation: How to Evolve Kubernetes Resource Management Model

Track: Software Defined Infrastructure: Kubernetes, Service Meshes, & Beyond

Location: Majestic Complex, 6th fl.

Duration: 11:50am - 12:40pm

Day of week: Wednesday

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Abstract

Built with Linux container and cgroup technologies, Kubernetes provides an efficient  framework for deploying different kinds of application workloads across multiple machines and compute platforms. Over the past five years, Kubernetes has evolved to support increasingly complex and diverse classes of applications, such as web services, databases, big data, and AI/ML workloads. As people are adopting Kubernetes to run even more diverse enterprise-class, cloud-native, and web-scalable workloads, we are seeing more requirements on improving the Kubernetes resource management model with better isolation, utilization, and performance consistency, yet provides a flexible and extensible framework for people to enable more hardware and workload-specific optimizations on Kubernetes.

In this talk, we will first provide an overview of the current Kubernetes resource model and best practice guidance on managing compute resources and specifying application resource requirements on Kubernetes. We will then discuss some recent and ongoing work on extending the Kubernetes resource model to provide better resource isolation, support more diverse hardware, facilitate fast and flexible application and resource scaling, and promote more consistent application performance across different compute platforms.

Speaker: Jiaying Zhang

Software Engineer @Google Kubernetes team

Jiaying Zhang is a software engineer at Google Kubernetes team. She has more than 10 years of experience in Linux system development on areas including NFS, ext4, kernel tracing, flash storage, and software-defined network. She has worked on Kubernetes for 2 years, focusing on improving compute resource management to better support more diverse workloads and hardware types.

Find Jiaying Zhang at

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