Container Cluster Model Development for Legacy Applications Integration in Scientific Software System

Trunov, A. S.; Voronova, L. I.; Voronov, Vyacheslav I.; Ayrapetov, Dmitriy P.

doi:10.1109/itmqis.2018.8525120

Cited by 13 publications

(5 citation statements)

References 8 publications

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“…Container engines such as Docker and Apptainer/Singularity allow applications to run on various computing environments while eliminating concerns about conflicting or missing dependencies 31,32 . These benefits make software containers suited to tackle issues relating to developing the scientific analysis workflows described above 33 . However, despite the benefits of containerization, only a small number of integrated neuroscience-specific or adaptable workflow systems support containerized distributed computing 6,[34][35][36] .…”

Section: Introductionmentioning

confidence: 99%

Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging

Renton,

Dao,

Johnstone

et al. 2024

Nat Methods

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Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can hamper the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (https://www.neurodesk.org/). Neurodesk includes a browseraccessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.

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Section: Introductionmentioning

confidence: 99%

Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging

Renton,

Dao,

Johnstone

et al. 2024

Nat Methods

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“…The reason for such an adoption is that application systems based on microservices architecture have the advantage of being easier to develop, deploy, and scale compared to monolithic architecture systems [13]. Containerization systems allow the configuration of the environment for software deployment in the shortest possible time, solving problems of integration of the most diverse applications [14].…”

Section: Theoretical Foundationmentioning

confidence: 99%

Software Aging in Container Orchestration Systems: An Assessment of Effects on Kubernetes

Tavares

Matos

Araújo

2022

Preprint

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Software Aging and Rejuvenation is a research topic that is being observed increasingly in the most diverse computing scenarios since the demand for reliability and availability of services has increased significantly. With the increasing use of containerized systems, there is also a need for the support of an orchestrator to ease management and reduce operational costs. In this paper, the behavior of Kubernetes software is evaluated, using both Minikube and K3S tools, while they manage pods in an accelerated lifetime experiment. Operations for creating and terminating pods are executed continuously, thus enabling us to observe the utilization of computing resources (e.g., CPU, memory, and I/O), the performance of the Minikube and K3S environments, and the response time of an application hosted in those environments. Software aging effects were observed in some conditions and for specific metrics, such as virtual memory usage, indicating a memory leak that is not fully cleared when the cluster is stopped. The issues found in this work may lead to system performance degradation and eventually compromise reliability and availability when the system crashes due to memory space exhaustion as well as full utilization of swap space on the hard disk.

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“…Consequently, a patchwork of linked legacy systems must be maintained, patched, and upgraded at escalating expense. The resulting architecture is frequently ill-equipped to meet present demands [8]. Therefore, the legacy systems could either be substituted entirely or developed and retained, which would involve rising costs and a decreasing investment return.…”

Section: Introductionmentioning

confidence: 99%

“…Because of a lack of internal involvement or a decision to allow someone else to take the risk, many major developments are contracted out, possibly contributing to the problem. In many cases, outsourcing may limit the company's control of the business [8,11].…”

Section: Introductionmentioning

confidence: 99%

Expediting Time to Market: Evaluating the Effects of Change Control Board Performance in Emerging Markets

Irfan,

Ali,

Hidayat-ur-Rehman

et al. 2023

Sustainability

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This study aims to assess how the performance of Change Control Boards (CCBs) influences the relationship between requirements uncertainty and the Time to Market (TTM) of software projects in emerging markets. We collected data through a structured questionnaire, conducting surveys in project-based IT organizations across various cities in Pakistan. This research adopts a quantitative approach, employing software project houses as the unit of analysis. We selected 38 software projects out of 50 using a multi-stage sampling method and analyzed the data using Smart PLS 4.0 and SPSS 23. The results reveal that requirements uncertainty has a significant impact on Time to Market (TTM) conditions. Our study concludes that the presence and effective performance of CCBs can substantially reduce TTM. Additionally, higher CCB performance can expedite TTM, particularly when requirements lack precision initially. The study underscores the profound influence of requirements uncertainty on TTM in software projects. It provides organizations with insights into the critical role of CCBs, the consequences of uncontrolled changes in the absence or ineffectiveness of CCBs, and how requirements uncertainty affects software project development and timelines. This research contributes to software management and product development processes by highlighting the importance of requirement engineering during the planning phase to address uncertainty issues and enhance CCB performance.

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Container Cluster Model Development for Legacy Applications Integration in Scientific Software System

Cited by 13 publications

References 8 publications

Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging

Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging

Software Aging in Container Orchestration Systems: An Assessment of Effects on Kubernetes

Expediting Time to Market: Evaluating the Effects of Change Control Board Performance in Emerging Markets

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