EMARS: Efficient Management and Allocation of Resources in Serverless

Saha, Aakanksha; Jindal, Sonika

doi:10.1109/cloud.2018.00113

Cited by 26 publications

(12 citation statements)

References 2 publications

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“…SUC A single client's event typically triggers the execution of multiple downstream functions that form a function composition. We differentiate between approaches for isolated functions [19,3,7,23], function chains [8,2], and complex compositions [5]. While a function chain executes multiple functions sequentially, a complex composition includes switching and parallel executions.…”

Section: Resultsmentioning

confidence: 99%

“…Each publication includes at least one configuration method in the context of serverless computing. Table 1 summarizes the final set of publications [19,5,3,8,20,22,2,7] in chronological order of appearance.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Ironically, configuring serverless systems "accurately" requires developers to understand a cloud platform's qualitysensitive configuration options hidden by the programming model's high abstraction. To this end, related work proposes configuration methods [19,8,2,6]. However, these configuration methods may not live up to developers' expectations, as they focus on accuracy but tend to neglect required cost and time.…”

Section: Introductionmentioning

confidence: 99%

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Synthesizing Configuration Tactics for Exercising Hidden Options in Serverless Systems

Kuhlenkamp

Werner

Tran

et al. 2022

Lecture Notes in Business Information Processing

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A proper configuration of an information system can ensure accuracy and efficiency, among other system objectives. Conversely, a poor configuration can have a significant negative impact on the system's performance, reliability, and cost. Serverless systems, which are comprised of many functions and managed services, especially risk exposure to misconfigurations, with many providerand platform-specific, often intransparent and 'hidden' settings. In this paper, we argue to pay close attention to the configuration of serverless systems to exercise options with known accuracy, cost and time. Based on a literature study and long-term serverless systems development experience, we present nine tactics to unlock potentially neglected and unknown options in serverless systems.

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Section: Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Synthesizing Configuration Tactics for Exercising Hidden Options in Serverless Systems

Kuhlenkamp

Werner

Tran

et al. 2022

Lecture Notes in Business Information Processing

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“…Nevertheless, we quantitatively compare with the most recent work in this area [19] which is primarily based on caching principles but with additional improvements for the serverless-specific case. Finally, prior approaches attempting to mitigate the cold start overhead, tend to either increase the capital cost, or increase the keep-alive cost [1,15,20,29,30,54,63,67]. In contrast, IceBreaker tries to address cold starts by reducing keepalive cost, while maintaining the same capital expenditure.…”

Section: Related Workmentioning

confidence: 99%

IceBreaker: warming serverless functions better with heterogeneity

Roy

Patel

Tiwari

2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

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Serverless computing, an emerging computing model, relies on łwarming upž 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 łkeep-alivež 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 ś opening up a new research avenue of serverless computing on heterogeneous servers for researchers and practitioners. CCS CONCEPTS• Computer systems organization → Cloud computing; ntier architectures; • General and reference → Performance.

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“…Work in [15,16] proposes a policy for deciding on function multi-tenancy, based on a predictive model of resource demands of each function. EMARS [29] tracks prior function executions and tries to predict the right amount of memory for each function. Kesidis [18] proposes to use prediction of the resource demands of functions to enable the provider to overbook functions on containers.…”

Section: Related Workmentioning

confidence: 99%

Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider

Shahrad,

Fonseca,

Goiri

et al. 2020

Preprint

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Function as a Service (FaaS) has been gaining popularity as a way to deploy computations to serverless backends in the cloud. This paradigm shifts the complexity of allocating and provisioning resources to the cloud provider, which has to provide the illusion of always-available resources (i.e., fast function invocations without cold starts) at the lowest possible resource cost. Doing so requires the provider to deeply understand the characteristics of the FaaS workload. Unfortunately, there has been little to no public information on these characteristics. Thus, in this paper, we first characterize the entire production FaaS workload from Microsoft Azure Functions. We show for example that most functions are invoked very infrequently, but there is an 8-order-of-magnitude range of invocation frequencies. Using observations from our characterization, we then propose a practical resource management policy that significantly reduces the number of function cold starts, while spending fewer resources than stateof-the-practice policies.

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EMARS: Efficient Management and Allocation of Resources in Serverless

Cited by 26 publications

References 2 publications

Synthesizing Configuration Tactics for Exercising Hidden Options in Serverless Systems

Synthesizing Configuration Tactics for Exercising Hidden Options in Serverless Systems

IceBreaker: warming serverless functions better with heterogeneity

Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider

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