Abstract
Serverless computing is currently receiving much attention from both academia and industry. It has a straightforward interface that abstracts the complex internal structure of cloud computing resource usage and configuration. The fine grained pay-per-use model of serverless computing can dramatically reduce the cost of using cloud computing resources for users. Thus, today more and more traditional cloud applications are moving to the serverless architecture. In serverless computing, functions executing in containers are the basic unit of scheduling. However, the impact of resource allocation on function performance in serverless platform is still not clear. It is very challenging to improve the function performance while reducing the resource costs in serverless platform. In this paper, we select several typical workloads in serverless and analyze the function performance by controlling the CPU and memory resources. Experimental results reveal the impact of resource allocation on the performance of different types of functions. We also classify the functions in serverless according to their dependence on CPU resources and memory resources.
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Acknowledgment
This work is supported by Key-Area Research and Development Program of Guangdong Province (NO. 2020B010164003), National Natural Science Foundation of China (No. 62072451), Shenzhen Basic Research Program (No. JCYJ2020 0109115418592), Science and Technology Development Fund of Macao S.A.R (FDCT) under number 0015/2019/AKP, and Youth Innovation Promotion Association CAS (NO. 2019349).
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Zhang, Y., Ye, K., Xu, CZ. (2022). An Experimental Analysis of Function Performance with Resource Allocation on Serverless Platform. In: Ye, K., Zhang, LJ. (eds) Cloud Computing – CLOUD 2021. CLOUD 2021. Lecture Notes in Computer Science(), vol 12989. Springer, Cham. https://doi.org/10.1007/978-3-030-96326-2_2
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DOI: https://doi.org/10.1007/978-3-030-96326-2_2
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