Applications executed in the cloud can exploit its elasticity features, varying dynamically the amount of leased resources so as to adapt to load variations and to guarantee quality of service. As auto-scaling has implications on execution costs, making optimal scaling choices is of paramount importance. This paper presents an analysis method based on offline benchmarking and simple models that allows to evaluate performance indexes useful to define scaling policies to be used by auto-scalers. The proposed approach relies on a fixed set of benchmarks, to be executed off-line and a set of models that enable prediction of the same performance indexes under different workload conditions, enabling the analyst to perform parameter analysis when defining an auto-scaling policy.
Auto-scaling Applications in the Cloud by Simple Indexes with Complex Loads / Catillo, M.; Ocone, L.; Rak, M.; Villano, U.. - 2020-:(2020), pp. 76-81. (Intervento presentato al convegno 29th IEEE International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE 2020 tenutosi a fra nel 2020) [10.1109/WETICE49692.2020.00023].
Auto-scaling Applications in the Cloud by Simple Indexes with Complex Loads
Rak M.;
2020
Abstract
Applications executed in the cloud can exploit its elasticity features, varying dynamically the amount of leased resources so as to adapt to load variations and to guarantee quality of service. As auto-scaling has implications on execution costs, making optimal scaling choices is of paramount importance. This paper presents an analysis method based on offline benchmarking and simple models that allows to evaluate performance indexes useful to define scaling policies to be used by auto-scalers. The proposed approach relies on a fixed set of benchmarks, to be executed off-line and a set of models that enable prediction of the same performance indexes under different workload conditions, enabling the analyst to perform parameter analysis when defining an auto-scaling policy.File | Dimensione | Formato | |
---|---|---|---|
wetice2020.pdf
non disponibili
Licenza:
Non specificato
Dimensione
7.91 MB
Formato
Adobe PDF
|
7.91 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.