Multi-objective Optimisation of Rolling Upgrade Allowing for Failures in Clouds

Abstract

Rolling upgrade is a practical industry technique for online updating of software in distributed systems. This paper focuses on rolling upgrade of software versions in virtual machine instances on cloud computing platforms, when various failures may occur. An operator can choose the number of instances that are updated in one round and system environments to minimise completion time, availability degradation, and monetary cost for entire rolling upgrade, and hence this is a multi-objective optimisation problem. To predict completion time in the presence of failures, we offer a stochastic model that represents the dynamics of rolling upgrade. To reduce the computational effort of decision making for large scale complex systems, we propose a technique that can find a Pareto set quickly via an upper bound of the expected completion time. Then an optimum of the original problem can be chosen from this set of potential solutions. We validate our approach to minimise the objectives, through both experiments in Amazon Web Service (AWS) and simulations.