scholarly journals A mixed-method empirical study of Function-as-a-Service software development in industrial practice

Author(s):  
Philipp Leitner ◽  
Erik Wittern ◽  
Josef Spillner ◽  
Waldemar Hummer

Function-as-a-Service (FaaS) describes cloud computing services that make infrastructure components transparent to application developers, thus falling in the larger group of “serverless” computing models. When using FaaS offerings, such as AWS Lambda, developers provide atomic and short-running code for their functions, and FaaS providers execute and horizontally scale them on- demand . Currently, there is no systematic research on how developers use serverless, what types of applications lend themselves to this model, or what architectural styles and practices FaaS-based applications are based on. We present results from a mixed-method study, combining interviews with advanced practitioners, a systematic analysis of grey literature, and a Web-based survey. We find that successfully adopting FaaS requires a different mental model, where systems are primarily constructed by composing pre-existing services, with FaaS often acting as the “glue” that brings these services together. Tooling availability and maturity, especially related to testing and deployment, remains a major difficulty. Further, we find that current FaaS systems lack systematic support for function reuse, and abstractions and programming models for building non-trivial FaaS applications are limited . We conclude with a discussion of implications for FaaS providers, software developers, and researchers.

2018 ◽  
Author(s):  
Philipp Leitner ◽  
Erik Wittern ◽  
Josef Spillner ◽  
Waldemar Hummer

Function-as-a-Service (FaaS) describes cloud computing services that make infrastructure components transparent to application developers, thus falling in the larger group of “serverless” computing models. When using FaaS offerings, such as AWS Lambda, developers provide atomic and short-running code for their functions, and FaaS providers execute and horizontally scale them on- demand . Currently, there is no systematic research on how developers use serverless, what types of applications lend themselves to this model, or what architectural styles and practices FaaS-based applications are based on. We present results from a mixed-method study, combining interviews with advanced practitioners, a systematic analysis of grey literature, and a Web-based survey. We find that successfully adopting FaaS requires a different mental model, where systems are primarily constructed by composing pre-existing services, with FaaS often acting as the “glue” that brings these services together. Tooling availability and maturity, especially related to testing and deployment, remains a major difficulty. Further, we find that current FaaS systems lack systematic support for function reuse, and abstractions and programming models for building non-trivial FaaS applications are limited . We conclude with a discussion of implications for FaaS providers, software developers, and researchers.


2016 ◽  
Vol 11 (3) ◽  
pp. 484-497 ◽  
Author(s):  
Joseph K. Liu ◽  
Man Ho Au ◽  
Xinyi Huang ◽  
Rongxing Lu ◽  
Jin Li

2021 ◽  
Author(s):  
Leonardo Reboucas de Carvalho ◽  
Alba Cristina Alves Melo ◽  
Aleteia Araujo

Protein sequence alignment is a task of great relevance in Bioinformatics and the Hirschberg algorithm is widely used for this task. This work proposes a framework for executing sequence alignment with the Hirschberg algorithm in different cloud computing services. In experiments, our framework was used to align HIV-1 protease sequences using different instances of AWS EC2 and different configurations of AWS Lambda functions.The results show that, for this application, there is a tradeoff between the expected execution time and the cost, e.g., in most cases AWS Lambda provides the best runtime, however at a higher USD cost. In this context, it is important to have a framework that helps in deciding which approach is most appropriate.


2014 ◽  
Vol 3 ◽  
pp. 94-112
Author(s):  
Angelė Pečeliūnaitė

The article analyses the possibility of how Cloud Computing can be used by libraries to organise activities online. In order to achieve a uniform understanding of the essence of technology SaaS, IaaS, and PaaS, the article discusses the Cloud Computing services, which can be used for the relocation of libraries to the Internet. The improvement of the general activity of libraries in the digital age, the analysis of the international experience in the libraries are examples. Also the article discusses the results of a survey of the Lithuanian scientific community that confirms that 90% of the scientific community is in the interest of getting full access to e-publications online. It is concluded that the decrease in funding for libraries, Cloud Computing can be an economically beneficial step, expanding the library services and improving their quality.


Author(s):  
Shengju Yang

In order to solve the trust problems between users and cloud computing service providers in cloud computing services, the existing trust evaluation technology and access control technology in the cloud computing service are analyzed. And the evaluation index of cloud computing is also analyzed. Users can calculate the relevant indicators of cloud computing service according to their own business goals, and choose the appropriate cloud computing services according to their own trust need. In addition, the reliability assessment method of users based on the service process is proposed. Cloud computing access control system can be used for user credibility evaluation, and it can handle user access requests according to user's creditability. In the study, a cloud computing service trust evaluation tool is designed, and the modeling and architecture designs of trust evaluation are also given. The effectiveness of the method is verified by experiments on cloud computing service evaluation methods.


2021 ◽  
Vol 11 (4) ◽  
pp. 1438
Author(s):  
Sebastián Risco ◽  
Germán Moltó

Serverless computing has introduced scalable event-driven processing in Cloud infrastructures. However, it is not trivial for multimedia processing to benefit from the elastic capabilities featured by serverless applications. To this aim, this paper introduces the evolution of a framework to support the execution of customized runtime environments in AWS Lambda in order to accommodate workloads that do not satisfy its strict computational requirements: increased execution times and the ability to use GPU-based resources. This has been achieved through the integration of AWS Batch, a managed service to deploy virtual elastic clusters for the execution of containerized jobs. In addition, a Functions Definition Language (FDL) is introduced for the description of data-driven workflows of functions. These workflows can simultaneously leverage both AWS Lambda for the highly-scalable execution of short jobs and AWS Batch, for the execution of compute-intensive jobs that can profit from GPU-based computing. To assess the developed open-source framework, we executed a case study for efficient serverless video processing. The workflow automatically generates subtitles based on the audio and applies GPU-based object recognition to the video frames, thus simultaneously harnessing different computing services. This allows for the creation of cost-effective highly-parallel scale-to-zero serverless workflows in AWS.


2021 ◽  
Vol 14 (1) ◽  
pp. 205979912098776
Author(s):  
Joseph Da Silva

Interviews are an established research method across multiple disciplines. Such interviews are typically transcribed orthographically in order to facilitate analysis. Many novice qualitative researchers’ experiences of manual transcription are that it is tedious and time-consuming, although it is generally accepted within much of the literature that quality of analysis is improved through researchers performing this task themselves. This is despite the potential for the exhausting nature of bulk transcription to conversely have a negative impact upon quality. Other researchers have explored the use of automated methods to ease the task of transcription, more recently using cloud-computing services, but such services present challenges to ensuring confidentiality and privacy of data. In the field of cyber-security, these are particularly concerning; however, any researcher dealing with confidential participant speech should also be uneasy with third-party access to such data. As a result, researchers, particularly early-career researchers and students, may find themselves with no option other than manual transcription. This article presents a secure and effective alternative, building on prior work published in this journal, to present a method that significantly reduced, by more than half, interview transcription time for the researcher yet maintained security of audio data. It presents a comparison between this method and a fully manual method, drawing on data from 10 interviews conducted as part of my doctoral research. The method presented requires an investment in specific equipment which currently only supports the English language.


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