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An Auto-Scaling Framework for Containerized Elastic Applications

Authors: Ye Tian; Guangtao Yue; Shiyou Qian; Minglu Li 0001;

An Auto-Scaling Framework for Containerized Elastic Applications

Abstract

Mechanisms for automatic resource provisioning in cloud environment have been widely studied. However, most current work are based on Virtual Machines(VMs) and few auto-scaling systems dedicated for containerized environment have been presented. This paper proposes an auto-scaler that caters for containerized elastic applications. We devise a hybrid scaling strategy based on a resource demand prediction model to meet Service Level Agreements(SLAs) in face of quickly varying workloads. We implemented our system in a private container-centric cloud environment and experimental results demonstrate that our auto-scaling framework out-performs existing rule-based approaches.

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Average
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