Dynamic load balancing resource scheduling method based on Kubernetes

Abstract

The invention discloses a dynamic load balancing resource scheduling method based on Kubernetes. According to the method, the dynamic load balancing algorithm is improved by combining the characteristics of the Kubernetes scheduling system, the scheduling algorithm is divided into a static scheduling part and a dynamic scheduling part, and the algorithm can still well maintain the load balancing of the system when the cluster environment changes. According to the container resource scheduling strategy of the Kubernetes, the problems that the scheduling strategy of the Kubernetes is single, andreasonable scheduling from a container to a machine node in a cluster cannot be achieved according to constraint scheduling requirements for specific factors such as a system kernel and a network transmission speed in container application are solved. And a dynamic load balancing scheduling strategy of migrating the Pod running on a certain working node to another new working node with a higher matching degree with the scheduling strategy is realized.

Description

technical field [0001] The invention belongs to the technical field of cloud computing, and relates to a dynamic load balancing resource scheduling method, in particular to a Kubernetes-based container resource scheduling method. Background technique [0002] The rapid development of cloud computing, big data, and mobile technology, coupled with the constant changes in business needs of enterprises, has led to the need to change the enterprise architecture at any time to meet business needs and keep up with the pace of technological updates. Undoubtedly, these burdens will fall on enterprise developers. How to efficiently coordinate among teams, quickly deliver products, quickly deploy applications, and meet enterprise business needs are problems that developers need to solve urgently. Docker technology can help developers solve these problems. [0003] Docker is an open source application container engine that allows developers to package their applications and dependenci...

AI Technical Summary

Problems solved by technology

[0007] 2. The data in the Pod is temporary. When the Pod is destroyed, the data in it will be lost, so the Pod needs to persist the data through the data volume

However, as time progresses, resources on working nodes change, Pod creation and deletion are affected by various factors, the scheduling choices made by the scheduler at the beginning of Pod creation may no longer be applicable at this moment.

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