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https://doi.org/10.21256/zhaw-1359| Publication type: | Conference paper |
| Type of review: | Peer review (publication) |
| Title: | Towards quantifiable boundaries for elastic horizontal scaling of microservices |
| Authors: | Ramírez López, Manuel Spillner, Josef |
| DOI: | 10.21256/zhaw-1359 10.1145/3147234.3148111 |
| Proceedings: | 10th International Conference on Utility and Cloud Computing Companion (UCC 2017) |
| Conference details: | 6th International Workshop on Clouds and (eScience) Applications Management (CloudAM 2017), Austin, USA, 5-8 December 2017 |
| Issue Date: | 2017 |
| Publisher / Ed. Institution: | Association for Computing Machinery |
| Publisher / Ed. Institution: | Austin |
| Language: | English |
| Subjects: | Microservices; Scalability; Replication; Optimization |
| Subject (DDC): | 004: Computer science |
| Abstract: | One of the most useful features of a microservices architecture is its versatility to scale horizontally. However, not all services scale in or out uniformly. The performance of an application composed of microservices depends largely on a suitable combination of replica count and resource capacity. In practice, this implies limitations to the efficiency of autoscalers which often overscale based on an isolated consideration of single service metrics. Consequently, application providers pay more than necessary despite zero gain in overall performance. Solving this issue requires an application-specific determination of scaling limits due to the general infeasibility of an application-agnostic solution. In this paper, we study microservices scalability, the auto-scaling of containers as microservice implementations and the relation between the number of replicas and the resulting application task performance. We contribute a replica count determination solution with a mathematical approach. Furthermore, we offer a calibration software tool which places scalability boundaries into declarative composition descriptions of applications ready to be consumed by cloud platforms. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/1395 |
| Fulltext version: | Accepted version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Computer Science (InIT) |
| Appears in collections: | Publikationen School of Engineering |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| elasticity-archive.pdf | 306.65 kB | Adobe PDF |  View/Open |
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Ramírez López, M., & Spillner, J. (2017). Towards quantifiable boundaries for elastic horizontal scaling of microservices. 10th International Conference on Utility and Cloud Computing Companion (UCC 2017). https://doi.org/10.21256/zhaw-1359
Ramírez López, M. and Spillner, J. (2017) ‘Towards quantifiable boundaries for elastic horizontal scaling of microservices’, in 10th International Conference on Utility and Cloud Computing Companion (UCC 2017). Austin: Association for Computing Machinery. Available at: https://doi.org/10.21256/zhaw-1359.
M. Ramírez López and J. Spillner, “Towards quantifiable boundaries for elastic horizontal scaling of microservices,” in 10th International Conference on Utility and Cloud Computing Companion (UCC 2017), 2017. doi: 10.21256/zhaw-1359.
RAMÍREZ LÓPEZ, Manuel und Josef SPILLNER, 2017. Towards quantifiable boundaries for elastic horizontal scaling of microservices. In: 10th International Conference on Utility and Cloud Computing Companion (UCC 2017). Conference paper. Austin: Association for Computing Machinery. 2017
Ramírez López, Manuel, and Josef Spillner. 2017. “Towards Quantifiable Boundaries for Elastic Horizontal Scaling of Microservices.” Conference paper. In 10th International Conference on Utility and Cloud Computing Companion (UCC 2017). Austin: Association for Computing Machinery. https://doi.org/10.21256/zhaw-1359.
Ramírez López, Manuel, and Josef Spillner. “Towards Quantifiable Boundaries for Elastic Horizontal Scaling of Microservices.” 10th International Conference on Utility and Cloud Computing Companion (UCC 2017), Association for Computing Machinery, 2017, https://doi.org/10.21256/zhaw-1359.
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