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With Great Freedom Comes Great Opportunity: Rethinking Resource Allocation for Serverless Functions
arXiv - CS - Performance Pub Date : 2021-05-31 , DOI: arxiv-2105.14845
Muhammad Bilal, Marco Canini, Rodrigo Fonseca, Rodrigo Rodrigues

Current serverless offerings give users a limited degree of flexibility for configuring the resources allocated to their function invocations by either coupling memory and CPU resources together or providing no knobs at all. These configuration choices simplify resource allocation decisions on behalf of users, but at the same time, create deployments that are resource inefficient. In this paper, we take a principled approach to the problem of resource allocation for serverless functions, allowing this choice to be made in an automatic way that leads to the best combination of performance and cost. In particular, we systematically explore the opportunities that come with decoupling memory and CPU resource allocations and also enabling the use of different VM types. We find a rich trade-off space between performance and cost. The provider can use this in a number of ways: from exposing all these parameters to the user, to eliciting preferences for performance and cost from users, or by simply offering the same performance with lower cost. This flexibility can also enable the provider to optimize its resource utilization and enable a cost-effective service with predictable performance. Our results show that, by decoupling memory and CPU allocation, there is potential to have up to 40% lower execution cost than the preset coupled configurations that are the norm in current serverless offerings. Similarly, making the correct choice of VM instance type can provide up to 50% better execution time. Furthermore, we demonstrate that providers can utilize different instance types for the same functions to maximize resource utilization while providing performance within 10-20% of the best resource configuration for each respective function.

中文翻译:

大自由带来大机遇:重新思考无服务器功能的资源分配

当前的无服务器产品通过将内存和 CPU 资源耦合在一起或根本不提供任何旋钮,为用户配置分配给其函数调用的资源提供了有限的灵活性。这些配置选择代表用户简化了资源分配决策,但同时会创建资源效率低下的部署。在本文中,我们对无服务器功能的资源分配问题采取了一种有原则的方法,允许以自动方式做出这种选择,从而实现性能和成本的最佳组合。特别是,我们系统地探索了解耦内存和 CPU 资源分配以及支持使用不同 VM 类型带来的机会。我们在性能和成本之间找到了丰富的权衡空间。提供商可以通过多种方式使用它:从向用户公开所有这些参数,到从用户那里获得对性能和成本的偏好,或者简单地以更低的成本提供相同的性能。这种灵活性还可以使提供商优化其资源利用率,并提供具有可预测性能的经济高效的服务。我们的结果表明,通过将内存和 CPU 分配解耦,与当前无服务器产品中的标准预设耦合配置相比,执行成本有可能降低多达 40%。同样,正确选择 VM 实例类型最多可将执行时间缩短 50%。此外,
更新日期:2021-06-01
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