Comparison of FaaS Orchestration Systems

López, Pedro; Sánchez-Artigas, Marc; Parı́s, Gerard; Barcelona-Pons, Daniel; Ollobarren, Alvaro Ruiz; Pinto, David Arroyo

doi:10.1109/ucc-companion.2018.00049

Cited by 41 publications

(33 citation statements)

References 5 publications

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“…Numerous works evaluate commercial and open source FaaS solutions [11,15,17] focusing on analysis of supported features and comparison based on the identified feature sets. Leitner et al [16] presents a mixed-method empirical study focusing on FaaS development in industrial practice, which combines a gray literature analysis with interviews and online questionnaire.…”

Section: Related Workmentioning

confidence: 99%

A Systematic Mapping Study on Engineering Function-as-a-Service Platforms and Tools

Yussupov

Breitenbücher

Leymann

et al. 2019

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing

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Function-as-a-Service (FaaS) is a novel cloud service model allowing to develop fine-grained, provider-managed cloud applications. In this work, we investigate which challenges motivate researchers to introduce or enhance FaaS platforms and tools. We use a systematic mapping study method to collect and analyze the relevant scientific literature, which helps us answering the three clearly-defined research questions. We design our study using well-established guidelines and systematically apply it to 62 selected publications. The collected and synthesized data provides useful insights into the main challenges that motivate researchers to work on this topic and can be helpful in identifying research gaps for future research.

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Section: Related Workmentioning

confidence: 99%

A Systematic Mapping Study on Engineering Function-as-a-Service Platforms and Tools

Yussupov

Breitenbücher

Leymann

et al. 2019

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing

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“…During our studies we also found that a large portion of the integration services based on serverless orchestration make heavy use of FaaS and act as a layer of abstraction to the service. An example of such a service would be AWS Step Functions [11,21].…”

Section: -Integrationmentioning

confidence: 99%

A Multivocal Literature Review of Function-as-a-Service (FaaS) Infrastructures and Implications for Software Developers

Grogan

Mulready

McDermott

et al. 2020

Communications in Computer and Information Science

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In this paper, we provide an analysis of Function as a Service (FaaS) infrastructures. FaaS is an important, emerging category of cloud computing, which requires that software applications are designed and deployed using distributed, highly-decoupled service-based architectures, one example of which is the microservices architecture paradigm. FaaS is associated with on-demand functionality and allows developers to build applications without the overhead associated with server management. As such, FaaS is a type of serverless provisioning model wherein a provider dynamically manages and allocates machine resources, with the developers deploying source code into a production environment. This research provides an analysis of scalability, cost, execution times, integration support, and the constraints associated with FaaS services provided by several vendors: AWS Lambda, Google Cloud Functions, and Azure Functions. We discuss the implications of the findings for software developers.

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“…General-purpose serverless orchestration frameworks include AWS Step Functions [6], Azure Durable Functions [7], Fission Workflows [14], and HyperFlow [16,47]. But these frameworks are not well-suited for supporting large, complex jobs, because they require manual workflow configurations (e.g., JSON) [46].…”

Section: Related Workmentioning

confidence: 99%

Wukong

Carver

Zhang

Wang

et al. 2020

Proceedings of the 11th ACM Symposium on Cloud Computing

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Executing complex, burst-parallel, directed acyclic graph (DAG) jobs poses a major challenge for serverless execution frameworks, which will need to rapidly scale and schedule tasks at high throughput, while minimizing data movement across tasks. We demonstrate that, for serverless parallel computations, decentralized scheduling enables scheduling to be distributed across Lambda executors that can schedule tasks in parallel, and brings multiple benefits, including enhanced data locality, reduced network I/Os, automatic resource elasticity, and improved cost effectiveness. We describe the implementation and deployment of our new serverless parallel framework, called Wukong, on AWS Lambda. We show that Wukong achieves near-ideal scalability, executes parallel computation jobs up to 68.17× faster, reduces network I/O by multiple orders of magnitude, and achieves 92.96% tenantside cost savings compared to numpywren.

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Comparison of FaaS Orchestration Systems

Cited by 41 publications

References 5 publications

A Systematic Mapping Study on Engineering Function-as-a-Service Platforms and Tools

A Systematic Mapping Study on Engineering Function-as-a-Service Platforms and Tools

A Multivocal Literature Review of Function-as-a-Service (FaaS) Infrastructures and Implications for Software Developers

Wukong

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