Proactive Serverless Function Resource Management

Hunhoff, Erika; Irshad, Shazal; Thurimella, Vijay; Tariq, Ali; Rozner, Eric

doi:10.1145/3429880.3430102

Cited by 12 publications

(5 citation statements)

References 13 publications

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“…Regarding resource management, Serverless platforms may be extended with a form of monitoring systems [28], which provides real-time information about the current resource utilization and, based on that information, limit the utilization or allocate more resources, when required. In order to solve cold starts, a solution may involve maintaining warm containers to prevent invocation delays [29]. What concerns Serverless scheduling, the main objective is to provide better execution times while minimizing cost.…”

Section: Discussionmentioning

confidence: 99%

Cloud Native Computing for Industry 4.0: Challenges and Opportunities

Gil¹,

Corujo

Pedreiras

2021

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )

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Cloud-based architectures are advantageous in aspects such as scalability, reliability and resource utilization efficiency, to name just a few, thus being considered one of the pillars of Industry 4.0. However, in this domain, cloud computing platforms are subject to specific requirements, namely in what concerns real-time performance, determinism and faulttolerance. This paper focuses on cloud native computing, which is an emerging and promising cloud-computing paradigm, specifically addressing its applicability to real-time systems. Firstly, it introduces the architecture of cloud native applications, discussing their principles, potential advantages and challenges. Then it addresses the opportunities and constraints of such technologies when applied to industrial real-time systems.

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Section: Discussionmentioning

confidence: 99%

Cloud Native Computing for Industry 4.0: Challenges and Opportunities

Gil¹,

Corujo

Pedreiras

2021

2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )

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“…At times the reuse of warm containers may even cause additional latencies for example, when already fetched data in a function instance is out-of-date and required database connections have already reverted by the time a new request arrives at the container. Mechanisms to freshen up the warm instances prior to use is of importance in such instances [64].…”

Section: Elements Of Resource Managementmentioning

confidence: 99%

A Holistic View on Resource Management in Serverless Computing Environments: Taxonomy and Future Directions

2022

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Serverless computing has emerged as an attractive deployment option for cloud applications in recent times. The unique features of this computing model include rapid auto-scaling, strong isolation, fine-grained billing options and access to a massive service ecosystem which autonomously handles resource management decisions. This model is increasingly being explored for deployments in geographically distributed edge and fog computing networks as well, due to these characteristics. Effective management of computing resources has always gained a lot of attention among researchers. The need to automate the entire process of resource provisioning, allocation, scheduling, monitoring and scaling, has resulted in the need for specialized focus on resource management under the serverless model. In this article, we identify the major aspects covering the broader concept of resource management in serverless environments and propose a taxonomy of elements which influence these aspects, encompassing characteristics of system design, workload attributes and stakeholder expectations. We take a holistic view on serverless environments deployed across edge, fog and cloud computing networks. We also analyse existing works discussing aspects of serverless resource management using this taxonomy. This article further identifies gaps in literature and highlights future research directions for improving capabilities of this computing model.

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“…The scheduler thus should take the availability of the data or the data serving delays into account. Hunhof et al [82] introduced freshen which allows developers or providers to proactively fetch data along with other runtime reuse features to reduce overheads when executing serverless functions. The scheduling policy of Cloudburst [138] also prioritizes data locality.…”

Section: Studiesmentioning

confidence: 99%

Serverless Computing: A Survey of Opportunities, Challenges, and Applications

2022

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The emerging serverless computing paradigm has attracted attention from both academia and industry. This paradigm brings benefits such as less operational complexity, a pay-as-you-go pricing model, and an auto-scaling feature. The paradigm opens up new opportunities and challenges for cloud application developers. In this paper, we present a comprehensive overview of the past development as well as the recent advances in research areas related to serverless computing. First, we survey serverless applications introduced in the literature. We categorize applications in eight domains and separately discuss the objectives and the viability of the serverless paradigm along with challenges in each of those domains. We then classify those challenges into nine topics and survey the proposed solutions. Finally, we present the areas that need further attention from the research community and identify open problems.

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Proactive Serverless Function Resource Management

Cited by 12 publications

References 13 publications

Cloud Native Computing for Industry 4.0: Challenges and Opportunities

Cloud Native Computing for Industry 4.0: Challenges and Opportunities

A Holistic View on Resource Management in Serverless Computing Environments: Taxonomy and Future Directions

Serverless Computing: A Survey of Opportunities, Challenges, and Applications

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