Kubernetes based capacitor cloud configuration and interaction method among modules of cloud configuration

Abstract

The invention discloses a Kubernetes based capacitor cloud configuration and an interaction method among modules of cloud configuration. The Kubernetes based capacitor cloud configuration comprises a processor, and a mirror image construction module, a data warehouse module, a load balancing module, a service discovery module and a container monitoring module connected with the processor; the mirror image construction module provides mirror image file making, storing and distributing services; the data warehouse module stores and processes data in a database of a cluster; the load balancing module carries out load balancing on calculating nodes in the Kubernetes cluster; the service discovery module obtains information of dynamic change of the calculating nodes in the Kubernetes cluster; and the container monitoring module collects and displays information of motion state of the calculating nodes in the Kubernetes cluster. The cloud configuration and the interaction method can be applied to container systems which need high availability and expansibility conveniently.

Description

technical field [0001] The invention relates to the field of cloud computing technology and containers, in particular to a Kubernetes-based container cloud architecture and an interaction method between modules thereof. Background technique [0002] With the rapid development of the mobile Internet, the number of netizens and the duration of surfing the Internet have increased dramatically, and the background structure of the website is also constantly changing to cope with the increasingly large access demand. The design of the server architecture, from the initial deployment of all services such as Web services and database services on a physical server, to the separation of database services and Web services, thereby improving the performance and security of the server, and then using load balancing technology to The load is distributed to multiple servers to reduce the pressure on a single server, and to the latest automatic scaling method, by monitoring the CPU and memo...

AI Technical Summary

Problems solved by technology

[0003] However, there are many problems in using traditional server and cloud computing technologies to realize auto-scaling architecture, which has led to the fact that auto-scaling has not been widely used

First of all, it takes a long time to deploy business modules to the server, and mobile Internet applications require business modules to be iteratively launched quickly, and frequent deployment and updates of business modules will waste a lot of manpower and material resources

At the same time, for massive access requests, traditional servers or cloud computing architectures cannot quickly start new service nodes, resulting in access delays and even system crashes

Because the architecture of traditional cloud computing technology basically adopts the virtual machine method, in some subdivided fields, its inherent defects lead to unsatisfactory application effects

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