DevSecOps Services: A Study of the Most Common and Rarest DevSecOps Services Available in 2022
Bibliographic record
Abstract
DevSecOps is an evolving set of practices within the prevalent DevOps paradigm that aims to include security at every stage of the development cycle. In order to understand how it has matured since its inception, we looked at a sample of 25 companies offering DevSecOps services to identify which services were most common and rarest. Multiple trends were identified, including a heavy lean towards DevSecOps services towards consultation and organizational adaptation. We also identified compliance to be a focus of many DevSecOps services. DevSecOps consultation and DevSecOps as a Service (DaaS) were identified as two of the most commonly available services in 2022, and isolation, SRE, SIEM, and orchestration were the rarest. Future studies on this subject might reveal different trends in the evolution of DevSecOps services, assuming DevSecOps hasn't been replaced by a more advanced paradigm.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".