Erlang: Application-Aware Autoscaling for Cloud Microservices

Author:

Sachidananda Vighnesh1ORCID,Sivaraman Anirudh2ORCID

Affiliation:

1. Google USA and Stanford University

2. New York University USA

Publisher

ACM

Reference57 articles.

1. Omid Alipourfard, Hongqiang Harry Liu, Jianshu Chen, Shivaram Venkataraman, Minlan Yu, and Ming Zhang. 2017. Cherrypick: Adaptively unearthing the best cloud configurations for big data analytics. In 14th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 17). 469--482.

2. Amazon. 2023. Amazon EKS - Managed Kubernetes Service. https://aws.amazon.com/eks/. (Accessed on 05/30/2020).

3. Peter Auer, Nicolo Cesa-Bianchi, and Paul Fischer. 2002. Finite-time analysis of the multiarmed bandit problem. Machine learning 47, 2 (2002), 235--256.

4. Michel Barbeau and Evangelos Kranakis. 2007. Principles of ad-hoc networking. John Wiley & Sons.

5. Michael Alan Chang, Aurojit Panda, Hantao Wang, Yuancheng Tsai, Rahul Balakrishnan, and Scott Shenker. 2021. AutoTune: Improving End-to-end Performance and Resource Efficiency for Microservice Applications. arXiv preprint arXiv:2106.10334 (2021).

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