MétaCan
Menu
Back to cohort
Record W4250837799 · doi:10.48009/1_iis_2021_136-148

IMPLEMENTATION OF DEVOPS PARADIGM TO DEPLOYMENT AND PROVISIONING OF MICROSERVICES

2021· article· en· W4250837799 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

VenueIssues in Information Systems · 2021
Typearticle
Languageen
FieldComputer Science
TopicSoftware System Performance and Reliability
Canadian institutionsBritish Columbia Institute of Technology
Fundersnot available
KeywordsMicroservicesDevOpsProvisioningSoftware deploymentComputer scienceParadigm shiftSoftware engineeringProcess managementBusinessOperating systemCloud computing

Abstract

fetched live from OpenAlex

Microservices architecture is widely used in the industry to deploy applications in terms of well-defined services along with DevOps paradigm to frequently release features. This paper describes how to incorporate some widely used DevOps tools for the deployment of micro-services. Amazon Web Services (AWS) Serverless architecture is used for the deployment of microservices using AWS Elastic Container Service. The process of deployment and provisioning of microservices using main features of AWS Elastic Container Service will be demonstrated and discussed in this paper with a simple example. We have applied and integrated DevOps tools/technologies to manage and deploy microservices. The example project is one of many projects' students use to master DevOps skills and practices in the course "DevOps Principles and Practices" using current technologies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.296
Teacher spread0.287 · 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