On Merits and Viability of Multi-Cloud Serverless
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
Serverless computing is a rapidly growing paradigm in the cloud industry that envisions functions as the computational building blocks of an application. Instead of forcing the application developer to provision cloud resources for their application, the cloud provider provisions the required resources for each function "under the hood." In this work, we envision virtual serverless providers (VSPs) to aggregate serverless offerings. In doing so, VSPs allow developers (and businesses) to get rid of vendor lock-in problems and exploit pricing and performance variation across providers by adaptively utilizing the best provider at each time, forcing the providers to compete to offer cheaper and superior services. We discuss the merits of a VSP and show that serverless systems are well-suited to cross-provider aggregation, compared to virtual machines. We propose a VSP system architecture and implement an initial version. Using experimental evaluations, our preliminary results show that a VSP can improve maximum sustained throughput by 1.2x to 4.2x, reduces SLO violations by 98.8%, and improves the total invocations' costs by 54%.
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 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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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