Migrating an application to the cloud environment requires non-functional properties consideration such as cost, performance and Quality of Service (QoS). Given the variety and the plethora of cloud offerings in addition with the consumption-based pricing models currently available in the cloud market, it is extremely complex to find the optimal deployment that fits the application requirements and provides the best QoS and cost trade-offs. In many cases the performance of these service offerings may vary depending on the congestion level, provider policies and how the application types that are intended to be executed upon them use the computing resources. A key challenge for customers before moving to Cloud is to know application behavior on cloud platforms in order to select the best-suited environment to host their application components in terms of performance and cost. In this paper, we propose a combined methodology and a set of tools that support the design and migration of enterprise applications to Cloud. Our tool chain includes: (i) the performance assessment of cloud services based on cloud benchmark results, (ii) a profiler/classifier mechanism that identifies the computing footprint of an arbitrary application and provides the best matching with a cloud service solution in terms of performance and cost, (iii) and a design space exploration tool, which is effective in identifying the deployment of minimum costs taking into account workload changes and providing QoS guarantees.

Evangelinou, A., Ciavotta, M., Ardagna, D., Kopaneli, A., Kousiouris, G., Varvarigou, T. (2018). Enterprise applications cloud rightsizing through a joint benchmarking and optimization approach. FUTURE GENERATION COMPUTER SYSTEMS, 78, 102-114 [10.1016/j.future.2016.11.002].

Enterprise applications cloud rightsizing through a joint benchmarking and optimization approach

Ciavotta, M;
2018

Abstract

Migrating an application to the cloud environment requires non-functional properties consideration such as cost, performance and Quality of Service (QoS). Given the variety and the plethora of cloud offerings in addition with the consumption-based pricing models currently available in the cloud market, it is extremely complex to find the optimal deployment that fits the application requirements and provides the best QoS and cost trade-offs. In many cases the performance of these service offerings may vary depending on the congestion level, provider policies and how the application types that are intended to be executed upon them use the computing resources. A key challenge for customers before moving to Cloud is to know application behavior on cloud platforms in order to select the best-suited environment to host their application components in terms of performance and cost. In this paper, we propose a combined methodology and a set of tools that support the design and migration of enterprise applications to Cloud. Our tool chain includes: (i) the performance assessment of cloud services based on cloud benchmark results, (ii) a profiler/classifier mechanism that identifies the computing footprint of an arbitrary application and provides the best matching with a cloud service solution in terms of performance and cost, (iii) and a design space exploration tool, which is effective in identifying the deployment of minimum costs taking into account workload changes and providing QoS guarantees.
Articolo in rivista - Articolo scientifico
BenchmarkingCloud applicationsQoSModel driven designPerformance predictionDesign space exploration
English
2018
78
102
114
reserved
Evangelinou, A., Ciavotta, M., Ardagna, D., Kopaneli, A., Kousiouris, G., Varvarigou, T. (2018). Enterprise applications cloud rightsizing through a joint benchmarking and optimization approach. FUTURE GENERATION COMPUTER SYSTEMS, 78, 102-114 [10.1016/j.future.2016.11.002].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/186531
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