The State of FaaS: An analysis of public Functions-as-a-Service providers
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866912009781510144 |
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| author | Ekwe-Ekwe, Nnamdi Amos, Lucas |
| author_facet | Ekwe-Ekwe, Nnamdi Amos, Lucas |
| contents | Serverless computing is a growing and maturing field that is the focus of much research, industry interest and adoption. Previous works exploring Functions-as-a-Service providers have focused primarily on the most well known providers AWS Lambda, Google Cloud Functions and Microsoft Azure Functions without exploring other providers in similar detail. In this work, we conduct the first detailed review of ten currently publicly available FaaS platforms exploring everything from their history, to their features and pricing to where they sit within the overall public FaaS landscape, before making a number of observations as to the state of the FaaS. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_03021 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The State of FaaS: An analysis of public Functions-as-a-Service providers Ekwe-Ekwe, Nnamdi Amos, Lucas Distributed, Parallel, and Cluster Computing Serverless computing is a growing and maturing field that is the focus of much research, industry interest and adoption. Previous works exploring Functions-as-a-Service providers have focused primarily on the most well known providers AWS Lambda, Google Cloud Functions and Microsoft Azure Functions without exploring other providers in similar detail. In this work, we conduct the first detailed review of ten currently publicly available FaaS platforms exploring everything from their history, to their features and pricing to where they sit within the overall public FaaS landscape, before making a number of observations as to the state of the FaaS. |
| title | The State of FaaS: An analysis of public Functions-as-a-Service providers |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2408.03021 |