LatEst: Vertical elasticity for millisecond serverless execution

Sfakianakis, Yannis; Marazakis, Manolis; Kozanitis, Christos; Bilas, Angelos

doi:10.1109/ccgrid54584.2022.00105

Cited by 3 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Researchers have recognized the significance of these requirements and proposed autoscaling solutions to optimize serverless functions or applications using a variety of approaches. For instance, Sfakianakis et al [16] suggested an autoscaler that dynamically provisions function resources (e.g., CPU) to minimize the spawning of new instances. Mahmoudi et al [17] proposed a performance model to assist application owners and serverless providers in determining optimal configurations for serverless applications that will be deployed in a real environment.…”

Section: Sla/qosmentioning

confidence: 99%

See 1 more Smart Citation

Autoscaling in Serverless Computing : Taxonomy and OpenChallenges

Jawaddi

Ismail

2023

Preprint

View full text Add to dashboard Cite

The popularity of serverless computing has been fueled by its operational simplicity, pay-per-use pricing model, and the ability to autoscale. However, there is a lack of comprehensive reviews that focus on the autoscaling context in serverless computing. In this paper, we address this gap by proposing a taxonomy of autoscaling properties for serverless computing. To gather relevant information, we review recent contributions on autoscaling in serverless computing from 2018 to 2022. Using the proposed taxonomy, we analyze the existing autoscaling solutions. Our analysis reveals that the scaling objectives explored by researchers are limited to certain elements, and the existing serverless autoscaling approaches do not provide guarantees that the scaling policies or strategies can meet the Service Level Agreement (SLA) requirements. We conclude by recommending open challenges from three perspectives: verification of autoscaling, energy-driven autoscaling, and anomaly-aware autoscaling. These challenges highlight the need for future research to address the limitations of existing autoscaling approaches and provide more robust and reliable autoscaling mechanisms for serverless computing.

show abstract

Section: Sla/qosmentioning

confidence: 99%

“…In the area of serverless computing, there is one existing work that uses control theory to estimate resources for autoscaling [16]. This work models the relationship between incoming workloads and required resource allocation using a feedback loop control.…”

Section: Control Theorymentioning

confidence: 99%