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Future Generation Computer Systems
Article . 2025 . Peer-reviewed
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Article . 2025 . Peer-reviewed
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Automated generation of deployment descriptors for managing microservices-based applications in the cloud to edge continuum

Authors: James DesLauriers; Jozsef Kovacs; Tamas Kiss; André Stork; Sebastian Pena Serna; Amjad Ullah;

Automated generation of deployment descriptors for managing microservices-based applications in the cloud to edge continuum

Abstract

With the emergence of Internet of Things (IoT) devices collecting large amounts of data at the edges of the network, a new generation of hyper-distributed applications is emerging, spanning cloud, fog, and edge computing resources. The automated deployment and management of such applications requires orchestration tools that take a deployment descriptor (e.g. Kubernetes manifest, Helm chart or TOSCA) as input, and deploy and manage the execution of applications at run-time. While most deployment descriptors are prepared by a single person or organisation at one specific time, there are notable scenarios where such descriptors need to be created collaboratively by different roles or organisations, and at different times of the application’s life cycle. An example of this scenario is the modular development of digital twins, composed of the basic building blocks of data, model and algorithm. Each of these building blocks can be created independently from each other, by different individuals or companies, at different times. The challenge here is to compose and build a deployment descriptor from these individual components automatically. This paper presents a novel solution to automate the collaborative composition and generation of deployment descriptors for distributed applications within the cloud-to-edge continuum. The implemented solution has been prototyped in over 25 industrial use cases within the DIGITbrain project, one of which is described in the paper as a representative example.

Keywords

Research Line: Modeling (MOD), Deployment, Orchestration, QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány, LTA: Monitoring and control of processes and systems, LTA: Scalable architectures for massive data sets, LTA: Machine intelligence, algorithms, and data structures (incl. semantics), Branche: Automotive Industry, Research Line: (Interactive) simulation (SIM), Descriptors, LTA: Interactive decision-making support and assistance systems, Internet of things (IoT), Microservices, Edge, Cloud computing, Industry, Digital twin (DT)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
Green
hybrid
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