DEVOPS PARADIGM -A PEDAGOGICAL APPROACH TO MANAGE AND IMPLEMENT IT PROJECT
Bibliographic record
Abstract
DevOps, the widely used term in software industry, integrates the Development and IT Operations activities to frequently deliver, deploy, and release quality software features.DevOps approach emphasizes collaboration among Developments and IT operations teams throughout System Development Life Cycle (SDLC).The DevOps process is supported by wide variety of tool chains for various phases of SDLC.There exist many DevOps models.However, in this paper authors use a simple four phase pedagogical models to demonstrate principles of DevOps.In this paper authors attempt to show how DevOps principles can effectively be used to manage and implement business problems in classroom setting.Specifically, DevOps methodology is applied to manage develop and implement a small web application.This pedagogical approach is specially aimed at students who do not have prior experiences and skillsets in applying DevOps methodology and associated toolsets to every stages of SDLC.At the conclusion of the project, students gained valuable insights on how to apply DevOps principles to business problems and to select and use commonly used state of the arts tools to plan, manage, build, test, monitor, deploy tasks at every stages of DevOps.The authors also discuss the limitations and practical issues related to implementing DevOps within classroom settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".