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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Accesso online: | https://arxiv.org/abs/2410.06721 |
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| _version_ | 1866913539050962944 |
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| author | Peri, Aristotelis Tsenos, Michail Kalogeraki, Vana |
| author_facet | Peri, Aristotelis Tsenos, Michail Kalogeraki, Vana |
| contents | In recent years, serverless computing, especially Function as a Service (FaaS), is rapidly growing in popularity as a cloud programming model. The serverless computing model provides an intuitive interface for developing cloud-based applications, where the development and deployment of scalable microservices has become easier and cost-effective. An increasing number of batch-processing applications are deployed as pipelines that comprise a sequence of functions that must meet their deadline targets to be practical. In this paper, we present our Hybrid Cloud Scheduler (HCS) for orchestrating the execution of serverless batch-processing pipelines deployed over heterogeneous infrastructures. Our framework enables developers to (i) automatically schedule and execute batch-processing applications in heterogeneous environments such as the private edge and public cloud serverless infrastructures, (ii) benefit from cost reduction through the utilization of their own resources in a private cluster, and (iii) significantly improves the probability of meeting the deadline requirements of their applications. Our experimental evaluation demonstrates the efficiency and benefits of our approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_06721 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Orchestrating the Execution of Serverless Functions in Hybrid Clouds Peri, Aristotelis Tsenos, Michail Kalogeraki, Vana Distributed, Parallel, and Cluster Computing In recent years, serverless computing, especially Function as a Service (FaaS), is rapidly growing in popularity as a cloud programming model. The serverless computing model provides an intuitive interface for developing cloud-based applications, where the development and deployment of scalable microservices has become easier and cost-effective. An increasing number of batch-processing applications are deployed as pipelines that comprise a sequence of functions that must meet their deadline targets to be practical. In this paper, we present our Hybrid Cloud Scheduler (HCS) for orchestrating the execution of serverless batch-processing pipelines deployed over heterogeneous infrastructures. Our framework enables developers to (i) automatically schedule and execute batch-processing applications in heterogeneous environments such as the private edge and public cloud serverless infrastructures, (ii) benefit from cost reduction through the utilization of their own resources in a private cluster, and (iii) significantly improves the probability of meeting the deadline requirements of their applications. Our experimental evaluation demonstrates the efficiency and benefits of our approach. |
| title | Orchestrating the Execution of Serverless Functions in Hybrid Clouds |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2410.06721 |