
We design and build FEAT, a new scaling approach that uses (1) cloud functions as interim processing resources to compensate for VM launch delays and (2) a reactive, knobless, auto-scaling algorithm that requires no pre-specified thresholds or parameters, making it robust against changing load. We implement FEAT on Amazon Web Services (AWS) and Microsoft Azure. Our evaluations clearly demonstrate the higher performance and robustness of FEAT in comparison to existing approaches.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 20 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
