Autoscaling is a task of major importance in the cloud computing domain as it directly affects both operating costs and customer experience. Although there has been active research in this area for over ten years now, there is still a significant gap between the proposed methods in the literature and the deployed autoscalers in practice. Hence, many research autoscalers do not find their way into production deployments. This paper describes six core challenges that arise in production systems that are still not solved by most research autoscalers. We illustrate these problems through experiments in a realistic cloud environment with a real-world multi-service business application and show that commonly used autoscalers have various shortcomings. In addition, we analyze the behavior of overloaded services and show that these can be problematic for existing autoscalers. Generally, we analyze that these challenges are only insufficiently addressed in the literature and conclude that future scaling approaches should focus on the needs of production systems.
@inproceedings{strasser2022autoscaling,
title = {{Why Is It Not Solved Yet? Challenges for Production-Ready Autoscaling}},
author = {Straesser, Martin and Grohmann, Johannes and von Kistowski, Jóakim and Eismann, Simon and Bauer, André and Kounev, Samuel},
year = {2022},
month = apr,
booktitle = {Proceedings of the 13th ACM/SPEC International Conference on Performance Engineering (ICPE)},
publisher = {ACM},
pages = {105–115},
url = {https://dl.acm.org/doi/10.1145/3489525.3511680},
note = {Best Industry Paper},
numpages = {11},
award = {true}
}