| Autor: |
Edwin F. Boza, Xavier Andrade, Jorge Cedeno, Jorge Murillo, Harold Aragon, Cristina L. Abad, Andres G. Abad |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Computers, Vol 9, Iss 1, p 14 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2073-431X |
| DOI: |
10.3390/computers9010014 |
| Popis: |
The research community has made significant advances towards realizing self-tuning cloud caches; notwithstanding, existing products still require manual expert tuning to maximize performance. Cloud (software) caches are built to swiftly serve requests; thus, avoiding costly functionality additions not directly related to the request-serving control path is critical. We show that serverless computing cloud services can be leveraged to solve the complex optimization problems that arise during self-tuning loops and can be used to optimize cloud caches for free. To illustrate that our approach is feasible and useful, we implement SPREDS (Self-Partitioning REDiS), a modified version of Redis that optimizes memory management in the multi-instance Redis scenario. A cost analysis shows that the serverless computing approach can lead to significant cost savings: The cost of running the controller as a serverless microservice is 0.85% of the cost of the always-on alternative. Through this case study, we make a strong case for implementing the controller of autonomic systems using a serverless computing approach. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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