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Record W4402096237 · doi:10.51594/csitrj.v5i8.1492

Assessing the transformative impact of cloud computing on software deployment and management

2024· article· en· W4402096237 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer Science & IT Research Journal · 2024
Typearticle
Languageen
FieldComputer Science
TopicCloud Computing and Resource Management
Canadian institutionsTD Bank Group
Fundersnot available
KeywordsSoftware deploymentCloud computingTransformative learningComputer scienceSoftwareSoftware as a serviceSoftware engineeringSoftware developmentOperating systemSociology

Abstract

fetched live from OpenAlex

Cloud computing has fundamentally transformed the landscape of software deployment and management, offering significant benefits and reshaping traditional approaches. This review explores the transformative impact of cloud computing on these domains, highlighting key changes and advantages. Firstly, cloud computing has revolutionized software deployment by introducing scalable and flexible infrastructure solutions. Unlike traditional onpremises systems that require significant upfront investment and ongoing maintenance, cloud platforms offer ondemand resources and payasyougo models. This shift enables organizations to deploy software rapidly, adapt to changing needs, and scale resources efficiently without the constraints of physical hardware. Additionally, cloud computing enhances software management through centralized control and automation. Cloud environments provide integrated management tools that streamline the deployment, monitoring, and maintenance of applications. These tools facilitate automated updates, patch management, and system backups, reducing the burden on IT teams and minimizing downtime. Furthermore, cloudbased management systems offer realtime visibility and analytics, allowing for proactive performance monitoring and troubleshooting. The collaborative nature of cloud computing also fosters improved development and deployment practices. Cloud platforms support DevOps methodologies by enabling continuous integration and continuous delivery (CI/CD) pipelines. This integration accelerates software development cycles, enhances collaboration among distributed teams, and ensures consistent and reliable deployments. Moreover, the cloud's global reach and accessibility break down geographical barriers, allowing organizations to deploy software across multiple regions effortlessly. This geographic flexibility enhances the user experience and ensures high availability and performance, regardless of the user's location. Despite these advancements, the transition to cloud computing presents challenges, including data security and compliance concerns. Organizations must implement robust security measures and adhere to regulatory requirements to protect sensitive information and maintain trust. In conclusion, cloud computing has had a profound impact on software deployment and management, offering scalable, flexible, and efficient solutions. Its transformative effects include streamlined operations, improved collaboration, and global accessibility. As cloud technology continues to evolve, organizations must navigate associated challenges while leveraging its benefits to drive innovation and efficiency in software management. Keywords: Management, Impact, Cloud Computing, Software Deployment, Assessing

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0060.000
Open science0.0030.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.070
GPT teacher head0.413
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it