IceBreaker: warming serverless functions better with heterogeneity

IceBreaker: warming serverless functions better with heterogeneity
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DOI:
10.1145/3503222.3507750
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发表时间:
2022-02
期刊:
Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems
影响因子:
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通讯作者:
Rohan Basu Roy;Tirthak Patel;Devesh Tiwari
Rohan Basu Roy;Tirthak Patel;Devesh Tiwari
中科院分区:
其他
文献类型:
--
作者:
Rohan Basu Roy;Tirthak Patel;Devesh Tiwari

文献摘要

相似文献

无服务器计算是一种新兴的计算模式,它依赖于在其预期执行之前的“预热”功能,以更快和更经济有效地为用户提供服务。不幸的是,预热功能可能是不准确的并且在预热期间导致昂贵的成本(即,保活成本)。在本文中,我们介绍了冰断路器,一种新的技术,减少了服务时间和“保活”的成本组成一个系统与异构节点(昂贵和便宜)。IceBreaker通过动态确定成本有效的节点类型来实现这一点,以根据函数下一次调用的时变概率来预热函数。通过采用异构性,IceBreaker允许在相同的成本预算下使用更多的节点,从而保持更多的功能,并减少高负载期间的等待时间。我们的真实系统评估证实,使用代表性的无服务器应用程序和行业级工作负载跟踪,IceBreaker将整体保持活动成本降低了45%,执行时间减少了27%。IceBreaker是第一个采用和利用混合昂贵和便宜节点的想法来改善无服务器功能的服务时间和保持活动成本的技术-为研究人员和从业者开辟了异构服务器上的无服务器计算的新研究途径。
Serverless computing, an emerging computing model, relies on "warming up" functions prior to its anticipated execution for faster and cost-effective service to users. Unfortunately, warming up functions can be inaccurate and incur prohibitively expensive cost during the warmup period (i.e., keep-alive cost). In this paper, we introduce IceBreaker, a novel technique that reduces the service time and the "keep-alive" cost by composing a system with heterogeneous nodes (costly and cheaper). IceBreaker does so by dynamically determining the cost-effective node type to warm up a function based on the function's time-varying probability of the next invocation. By employing heterogeneity, IceBreaker allows for more number of nodes under the same cost budget and hence, keeps more number of functions warm and reduces the wait time during high load. Our real-system evaluation confirms that IceBreaker reduces the overall keep-alive cost by 45% and execution time by 27% using representative serverless applications and industry-grade workload trace. IceBreaker is the first technique to employ and leverage the idea of mixing expensive and cheaper nodes to improve both service time and keep-alive cost for serverless functions -- opening up a new research avenue of serverless computing on heterogeneous servers for researchers and practitioners.