Cloud resource scheduling method and system based on Kubernetes

Abstract

The invention provides a cloud resource scheduling method and system based on Kubernetes. The method comprises the following steps: creating a Pod according to a resource object creation request, so as to record a type of required schedulers in the resource object creation request into a configuration file of created Pod; after the created Pod is monitored, selecting schedulers from a pre-deployed scheduler group of a required scheduler type, and updating identifiers of the selected schedulers to a configuration file of the Pods, wherein the scheduler group comprises a plurality of schedulers of the same type; after the selected schedulers listen to their own own identifiers, determining a cluster node allocated to the Pod and sending a binding request; after the binding request is received through an access controller, verifying that resources still can meet requirements of information of required resources, and recording the identifiers of the cluster nodes to the Pod; after the corresponding cluster nodes monitor that the Pod records the identifiers of the cluster nodes, starting the Pod, and creating a corresponding container. According to the scheme, more schedulers can schedule cloud resources in parallel, and the resource scheduling efficiency is improved.

Description

technical field [0001] The present invention relates to the technical field of cloud resource scheduling, in particular to a Kubernetes-based cloud resource scheduling method and system. Background technique [0002] The container cloud platform is a cloud resource management platform based on container technology. Among the resource scheduling tasks that need to be executed, many tasks do not need to communicate with each other or do not need to be synchronized. For example, tasks based on the MapReduce framework in big data scenarios. If there is only a single scheduler, the resource scheduling efficiency will be relatively low when the scale of the cloud resource cluster is relatively large. [0003] Native Kubernetes uses a single scheduler to process user tasks by default. Although the new multi-scheduler function allows multiple schedulers to work at the same time, the number and type of schedulers are fixed, and each type of scheduler only one. Contents of the inve...

AI Technical Summary

Problems solved by technology

If there is only a single scheduler, the resource scheduling efficiency will be relatively low when the scale of the cloud resource cluster is relatively large

[0003] Native Kubernetes uses a single scheduler to process user tasks by default. Although the new multi-scheduler function allows multiple schedulers to work at the same time, the number and type of schedulers are fixed, and each type of scheduler only one

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