HoloScale: horizontal and vertical scaling of cloud resources

Elastic and scalable compute resources are a fundamental part of cloud computing. Efficient management of cloud resources is crucial in order to provide high quality services and applications. In this work we present a novel method for scaling cloud resources and provide stability guarantees. We do this by leveraging ideas and concepts from classic control theory, namely mid-range control and combine horizontal scaling and vertical scaling in a novel way. Horizontal scaling is typically when one adds/removes whole unites of resources (e.g., virtual machines or containers), while vertical scaling is when one grows/shrinks already allocated resources (e.g., making a deployed virtual machine larger/smaller). Each methods has their own trade-offs: i) horizontal scaling is often slow and coarse-grained, but can scale over a large range, and ii) vertical scaling is often quick and smooth, but has limited range. The proposed algorithm is called HoloScale, which leverages the strengths of both scaling mechanisms, without the draw-backs. The method is capable of scaling smoothly, quickly, and over a large range. By using core concepts from control theory, we show that systems managed by the HoloScale algorithm are stable in the presence of time-varying scaling delays.