Auto-Scaling Web Application in Docker Based on Gray Prediction

摘要

The on-demand use and the elastic scaling feature of cloud computing make more and more companies deploy web applications on cloud platforms. True elasticity and cost-effectiveness in the pay-per-use cloud business model, however, have not yet been achieved. To address this challenge, we propose an algorithm which can auto-scaling web application in docker. We use docker container technology to deploy web applications and add or delete docker containers to adjust web applications resources. The use of dynamic weighted average method to calculate the weight of web application indicators combined with the gray prediction algorithm to predict container scale up and down. Experimental results show that the algorithm in this paper can achieve better results.