@inproceedings{pavlenko2024vertically,
author = {Pavlenko, Anna and Cahoon, Joyce and Zhu, Yiwen and Kroth, Brian and Nelson, Michael and Carter, Andrew and Liao, David and Wright, Travis and Camacho-Rodríguez, Jesús and Saur, Karla},
title = {Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud},
booktitle = {SIGMOD},
year = {2024},
month = {June},
abstract = {Kubernetes has emerged as a prominent open-source platform for managing cloud applications, including stateful databases. These monolithic applications rely on vertical scaling, adjusting CPU cores based on load fluctuations. However, our analysis of Kubernetes-based Database-as-a-Service (DBaaS) offerings at Microsoft revealed that many customers consistently over-provision resources for peak workloads, neglecting cost-saving opportunities through resource scale-down. We found that there is a gap in the ability of existing vertical autoscaling tools to minimize resource slack and respond promptly to throttling, leading to increased costs and impacting crucial metrics such as throughput and availability.

To address this challenge, we propose CaaSPER, a vertical autoscaling algorithm that blends reactive and proactive strategies. By dynamically adjusting CPU resources, CaaSPER minimizes resource slack, maintains optimal CPU utilization, and reduces throttling. Importantly, customers have the flexibility to prioritize either cost savings or high performance based on their preferences. Extensive testing demonstrates that CaaSPER effectively reduces throttling and keeps CPU utilization within target levels. CaaSPER is designed to be application-agnostic and platform-agnostic, with potential for extension to other applications requiring vertical autoscaling.},
url = {http://approjects.co.za/?big=en-us/research/publication/caasper-vertical-autoscaling/},
note = {to appear},
}