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RADON: rational decomposition and orchestration for serverless computing

G. Casale, M. Artač, W.-J. van den Heuvel, A. van Hoorn, P. Jakovits, F. Leymann, M. Long, V. Papanikolaou, D. Presenza, A. Russo, S. N. Srirama, D. A. Tamburri (+2 others)
2019 SICS Software-Intensive Cyber-Physical Systems  
In this vision paper, we present the research agenda of the RADON project (, which aims to develop a model-driven DevOps framework for creating and managing applications based on  ...  Emerging serverless computing technologies, such as function as a service (FaaS), enable developers to virtualize the internal logic of an application, simplifying the management of cloud-native services  ...  This is a richer setting compared to that of a traditional methodology, as one can envision different life cycles for serverless functions, microservices and data pipelines.  ... 
doi:10.1007/s00450-019-00413-w fatcat:q7mf6hhc7jauxfngrg57tjks7a

Performance Engineering for Microservices and Serverless Applications: The RADON Approach - Artifacts

Alim U. Gias, Andre van Hoorn, Lulai Zhu, Giuliano Casale, Thomas F. Düllmann, Michael Wurster
2020 Zenodo  
Artifacts for the tutorial on "Performance Engineering for Microservices and Serverless Applications: The RADON Approach", presented at the 11th ACM/SPEC International Conference on Performance Engineering  ...  Challenge: runtime operations and delivery • How to deliver in DevOps fashion hybrid serverless-based applications? • How to abstract events in multi-cloud environments?  ...  for Runtime Resource Management of Microservices Challenges -LQN Modeling • In-house application?  ... 
doi:10.5281/zenodo.3670013 fatcat:dre3pywaubb6zb62w2pwwlndkq


2021 Issues in Information Systems  
Amazon Web Services (AWS) Serverless architecture is used for the deployment of microservices using AWS Elastic Container Service.  ...  This paper describes how to incorporate some widely used DevOps tools for the deployment of micro-services.  ...  Most of the serverless tools can be conFigd as a code, and therefore are useful for DevOps practices.  ... 
doi:10.48009/1_iis_2021_136-148 fatcat:4snv5jmmd5dbrdpfkxzqej7bku

Anomaly Detection in a Large-scale Cloud Platform [article]

Mohammad Saiful Islam, William Pourmajidi, Lei Zhang, John Steinbacher, Tony Erwin, Andriy Miranskyy
2021 arXiv   pre-print
After running the system for a year, we observed that the proposed solution frees the DevOps team's time and human resources from manually monitoring thousands of Cloud components.  ...  To address the challenge, we designed and implemented an automated monitoring system for the IBM Cloud Platform.  ...  Our challenges Maintaining an adequate response time of IBM Cloud Platform/Console application components is crucial for the DevOps teams.  ... 
arXiv:2010.10966v2 fatcat:l6moyl3z3jfhfgr7wmrs4sckhq

Quality-Aware DevOps research: where do we stand?

Ahmad Alnafessah, Alim Ul Gias, Runan Wang, Lulai Zhu, Giuliano Casale, Antonio Filieri
2021 IEEE Access  
Our analysis also outlines possible directions for future work in quality-aware DevOps, looking in particular at AI for DevOps and DevOps for AI software.  ...  A significant volume of activity has been carried out in recent years with the aim of coupling DevOps stages with tools and methods to improve the quality of the produced software and the underpinning  ...  For this reason, quality assurance in DevOps is often a synonym of continuous functional testing methods to check the correctness of application prior to deployment.  ... 
doi:10.1109/access.2021.3064867 fatcat:3jceiw4mifgy7i7hu6vvleryjm

Developing Self-Adaptive Microservice Systems: Challenges and Directions [article]

Nabor C. Mendonca, Pooyan Jamshidi, David Garlan, Claus Pahl
2019 arXiv   pre-print
This article identifies key challenges for the development of microservice applications as self-adaptive systems, using a cloud-based intelligent video surveillance application as a motivating example.  ...  It also suggests potential new directions for addressing most of the identified challenges by leveraging existing microservice practices and technologies.  ...  This operation could be useful to implement a canary release pipeline for each of the video surveillance services.  ... 
arXiv:1910.07660v2 fatcat:tdxseu3vsffw7i24tnkcqp5p3y


Thomas F. Düllmann, André van Hoorn, Vladimir Yussupov, Pelle Jakovits, Mainak Adhikari
2022 Companion of the 2022 ACM/SPEC International Conference on Performance Engineering  
We demonstrate CTT's workflow, its architecture, as well as its application to DevOps-oriented load testing and load testing of data pipelines.  ...  CTT employs the OASIS TOSCA Standard to enable end-to-end support for continuous testing of cloud-based applications.  ...  We thank Andrea Janes from the Free University of Bozen-Bolzano for his support in integrating CTT with PPTAM.  ... 
doi:10.1145/3491204.3527484 fatcat:gl44mku6rngpzailrb7frvue4u

Reproducible and Portable Big Data Analytics in the Cloud [article]

Xin Wang, Pei Guo, Xingyan Li, Jianwu Wang, Aryya Gangopadhyay, Carl E. Busart, Jade Freeman
2022 arXiv   pre-print
The first is how to automate end-to-end execution of analytics including environment provisioning, analytics pipeline description, pipeline execution and resource termination.  ...  To tackle these problems, we leverage serverless computing and containerization techniques for automatic scalable execution and reproducibility, and utilize the adapter design pattern to enable application  ...  Each component in the application pipeline is implemented as a serverless function and triggered by the events it listens to.  ... 
arXiv:2112.09762v2 fatcat:zbrlopjvkrhm5ho5mm5zpv2ryu

Understanding the Context of IoT Software Systems in DevOps [article]

Igor Muzetti Pereira, Tiago Garcia de Senna Carneiro, Eduardo Figueiredo
2021 arXiv   pre-print
) perceived pipeline for this kind of software development.  ...  We rely on a Systematic Literature Review to investigate the relations of DevOps in IoT software systems.  ...  Often, the beginning of a DevOps implementation is the application of an automated CI/CD pipeline (Continuous Integration and Delivery).  ... 
arXiv:2104.10147v2 fatcat:mg5ghqmrpvht7an67tvv3n6wue

Towards a Serverless Platform for Edge AI

Thomas Rausch, Waldemar Hummer, Vinod Muthusamy, Alexander Rashed, Schahram Dustdar
2019 USENIX Workshop on Hot Topics in Edge Computing  
This paper proposes a serverless platform for building and operating edge AI applications.  ...  Furthermore, we demonstrate the limitations of current serverless function schedulers, and present the current state of our prototype.  ...  Through experimental analysis we uncover some of the major limitations of current state-of-the-art serverless platforms for supporting edge AI applications, and then present our approach for building a  ... 
dblp:conf/hotedge/RauschHMRD19 fatcat:5fqfny6byzgllp66ttmurr4fea

QFaaS: A Serverless Function-as-a-Service Framework for Quantum Computing [article]

Hoa T. Nguyen, Muhammad Usman, Rajkumar Buyya
2022 arXiv   pre-print
Recent breakthroughs in quantum hardware are creating opportunities for its use in many applications.  ...  To alleviate these challenges, we propose QFaaS, a novel Quantum Function-as-a-Service framework, which leverages the advantages of the serverless model and the state-of-the-art software engineering approaches  ...  Inspired by the advantages of the Serverless and DevOps models, combined with the Quantum Cloud Computing paradigm, we have designed and implemented QFaaS with a set of essential features for creating  ... 
arXiv:2205.14845v1 fatcat:c7gw6ns355g7bcwdrlkzozy3ji

On the Future of Cloud Engineering [article]

David Bermbach, Abhishek Chandra, Chandra Krintz, Aniruddha Gokhale, Aleksander Slominski, Lauritz Thamsen, Everton Cavalcante, Tian Guo, Ivona Brandic, Rich Wolski
2021 arXiv   pre-print
advances, and identify both the inherent technical challenges and research opportunities for the future of cloud computing in general and cloud engineering in particular.  ...  offerings, developer productivity enhancement tools, and new application classes as well as the manifestation of cloud functionality closer to the user at the edge.  ...  use a DevOps model [13] .  ... 
arXiv:2108.08685v1 fatcat:mlalfa657zbappkvl3i2cyionu

Automated Data-Ops for Community-Driven Flood Monitoring

Diego Pajarito Grajales, João Porto de Albuquerque
2022 Zenodo  
We discuss the challenges and efforts of setting data pipelines for a community-driven monitoring network in Brazil.  ...  Automation through DataOps might facilitate the development and operation of heterogeneous data flows. However, its implementation implies a steep learning curve and requirements difficult to meet.  ...  Implementing DevOps for citizen science stands as a novel contribution that implies a critical review of data flows and the potential evolution of data integration within community-led projects.  ... 
doi:10.5281/zenodo.6408410 fatcat:ywd3362dqrakxmuik5daxln2fa

Integration of DevOps practices on a noise monitor system with CircleCI and Terraform

Esteban Elias Romero, Carlos David Camacho, Carlos Enrique Montenegro, Óscar Esneider Acosta, Rubén González Crespo, Elvis Eduardo Gaona, Marcelo Herrera Martínez
2022 ACM Transactions on Management Information Systems  
The aim of this paper is to document the implementation of some DevOps practices such as IaC, continuous integration and deployment, code quality control and collaboration on a noise monitor system to  ...  The final result is a set of automated pipelines which represents the entire integration and deployment cycle of the software integrated with platforms to improve quality and maintainability of the software  ...  One of the latest implementations of WSN in 2020 is [27] where the application of a Wireless Acoustic Sensor Network is proposed for the long-term analysis of psychoacoustic parameters of the acoustic  ... 
doi:10.1145/3505228 fatcat:swwrsgf3ozhh5jooctwyiewfim

Serverless on FHIR: Deploying machine learning models for healthcare on the cloud [article]

Bell Raj Eapen, Kamran Sartipi, Norm Archer
2020 arXiv   pre-print
We call this architecture Serverless on FHIR and propose this as a standard to deploy digital health applications that can be consumed by downstream systems such as EMRs and visualization tools.  ...  Machine Learning (ML) plays a vital role in implementing digital health. The advances in hardware and the democratization of software tools have revolutionized machine learning.  ...  The uniform format of the input and output allows the chaining of ML models as a pipeline.  ... 
arXiv:2006.04748v1 fatcat:ivk2yffpynbkndbjry7av5ma3m
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