Comparing Pacemaker with OpenSAF for Availability Management in the Cloud
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.
Bibliographic record
Abstract
Availability is an important non-functional requirement for carrier grade services. Cloud computing is gaining in popularity but availability remains one of its main challenges in order to convince carrier grade service providers to migrate to the cloud. Several solutions, including Pacemaker/Corosync, have been proposed for managing the availability of cloud systems. On the other hand, OpenSAF, an open source middleware for availability management, has been successfully used in the cluster environment and initial experiments have demonstrated its potential for cloud systems. In this paper we describe some further experiments we performed for comparing Pacemaker/Corosync to OpenSAF from three different perspectives: availability, performance overhead and level of application integration difficulty. We also provide some analysis.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it