Making Cloud Spot Instance Interruption Events Visible

摘要

Public cloud computing providers offer a surplus of computing resources at a lower price with a service of a spot instance. Despite the possible great cost savings from using spot instances, sudden resource interruption can occur as resource demand changes. To help users estimate cost savings and the possibility of interruption when using spot instances, vendors provide diverse datasets. However, the effectiveness of using the datasets has not yet been quantitatively evaluated, and many users still rely on the guess when choosing spot instances. To help users lower the chance of interruption of the spot instance for reliable usage, in this paper, we thoroughly analyze various datasets of the spot instance and present the feasibility for value prediction. Then, to measure how the public datasets reflect real-world spot instance interruption events, we conduct real-world experiments for spot instances of AWS, Azure, and Google Cloud. Combining the dataset analysis, modeling, and the real-world spot instance interruption experiment, we present a significant improvement in reducing the possibility of interruption events.