FaaStest - Machine Learning Based Cost and Performance FaaS Optimization

Horovitz, Shay; Amos, Roei; Baruch, Ohad; Cohen, Tomer; Oyar, Tal; Deri, Afik

doi:10.1007/978-3-030-13342-9_15

Cited by 15 publications

(12 citation statements)

References 10 publications

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“…Serverless computing runs function in a limited and short execution time, while there are some tasks might require long execution time. This does not support long execution running, since these functions are stateless, which means that if the function is paused it cannot be resumed again [11,202,234,280].…”

Section: Long-runningmentioning

confidence: 99%

“…This issue makes the customers dependent on the serverless provider for products and services, and the customers cannot easily use different vendors in the future without substantial cost. Thus, customers have to wait on the serverless provider for additional services [9,130,202].…”

Section: Vendor Lock-inmentioning

confidence: 99%

“…Therefore, reducing the cold start penalties will help cloud providers in the first place and hence customers. The authors in [202] proposed FaaStest an autonomous approach based on machine learning to capture the function call behavior and then dynamically select the optimal ones. This technique could reduce the cold start by 90%.…”

Section: Function Startupmentioning

confidence: 99%

“…It is crucial to implement solutions that offer cost-effective computing resources. FaStest reduced the cost by 50% via learning the behavioral pattern of functions using machine learning [202]. Price estimation has a great impact on selecting the most optimal provider.…”

Section: Pricingmentioning

confidence: 99%

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Survey on serverless computing

2021

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Serverless computing has gained importance over the last decade as an exciting new field, owing to its large influence in reducing costs, decreasing latency, improving scalability, and eliminating server-side management, to name a few. However, to date there is a lack of in-depth survey that would help developers and researchers better understand the significance of serverless computing in different contexts. Thus, it is essential to present research evidence that has been published in this area. In this systematic survey, 275 research papers that examined serverless computing from well-known literature databases were extensively reviewed to extract useful data. Then, the obtained data were analyzed to answer several research questions regarding state-of-the-art contributions of serverless computing, its concepts, its platforms, its usage, etc. We moreover discuss the challenges that serverless computing faces nowadays and how future research could enable its implementation and usage.

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Section: Long-runningmentioning

confidence: 99%

Section: Vendor Lock-inmentioning

confidence: 99%

Section: Function Startupmentioning

confidence: 99%

Section: Pricingmentioning

confidence: 99%

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Survey on serverless computing

2021

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“…This work aims to investigate this proposition and provide evidence towards the cost efficiency of such hybrid, that is mixed FaaS and VMaaS, deployment scenarios for different kinds of load patterns. The realizability and efficacy of this position is already demonstrated by recent works like [8] and [9]. However, in contrast to these approaches, we focus on providing system owners with the means to decide whether and under which conditions such a deployment scenario is appropriate, rather than starting with the assumption that this is so.…”

Section: Introductionmentioning

confidence: 99%

Cost efficiency under mixed serverless and serverful deployments

Reuter

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Andrikopoulos

2020

2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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Time‐cost efficient memory configuration for serverless workflow applications

Fan

2022

Concurrency and Computation

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Recently, workflow applications are increasingly migrated to Function-as-a-Service platforms which are easy to manage, highly-scalable, and pay-as-you-go. Meanwhile, users face challenges in migration of serverless applications because of the lack of efficient algorithm for workflow memory configuration to optimize the performance. To this end, this article proposes a heuristic urgency-based algorithm UWC and a meta-heuristic hybrid algorithm BPSO to tackle the time-cost tradeoff. UWC sorts functions and allocates each function an appropriate memory size by greedy strategy. BPSO hybridizes particle swarm optimization as well as beetle antennae search algorithm to guide particles to search directionally and utilizes nonlinear inertia weight to avoid local premature convergence. Extensive experiments with classical serverless application demonstrate that UWC and BPSO are very competitive in comparison with existing algorithms as they can find the optimal workflow memory configuration.

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FaaStest - Machine Learning Based Cost and Performance FaaS Optimization

Cited by 15 publications

References 10 publications

Survey on serverless computing

Survey on serverless computing

Cost efficiency under mixed serverless and serverful deployments

Time‐cost efficient memory configuration for serverless workflow applications

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