Load prediction based Docker container dynamic scheduling method

Abstract

The invention provides a load prediction based Docker container dynamic scheduling method. The method includes: acquiring Docker container load data by a Docker container load monitoring module; storing the load data in a time series database; enabling a Docker container load prediction module to acquire and process the load data from the time series database, analyze the load data by the aid of an ARIMA model and generate a load predicated value; finally, automatically expanding quantity of Docker containers in a Docker container cluster according to the load predicated value by a Docker container scheduling module. By application of a load prediction technique to the field of Docker container scheduling, automatic expansion of the Docker container cluster according to real-time load conditions is realized, the problem of inadequate load capacity in an operating stage due to failure of the Docker container cluster in automatic resource regulation according to load conditions is effectively solved, and usability of the Docker container cluster is improved.

Description

technical field [0001] The invention belongs to the technical field of dynamic scheduling of Docker containers, and in particular provides a dynamic scheduling method of Docker containers based on load prediction. Background technique [0002] The microservice architecture splits an application into multiple independent services with business attributes. Each service runs in an independent process, and the services cooperate with each other through a lightweight communication mechanism to provide business value to end users. The deployment methods of applications based on the microservice architecture include manual deployment and script deployment based on cloud platforms, and image deployment based on Docker containers is currently a relatively mainstream method. [0003] As an open source application container engine, Docker containers enable developers to package applications and their dependencies into portable Docker containers, and then publish the Docker containers t...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to apply the load forecasting technology to the dynamic scheduling of Docker containers, solve the problem that the current Docker container clusters cannot automatically adjust resources due to load conditions and have insufficient load capacity in the running stage, and provide users of Docker container clusters with a load forecasting based The Docker container dynamic scheduling method

Images