The lambda architectural pattern allows to overcome some limitations of data processing frameworks. It builds on the methodology of having two different data processing streams on the same system: a real time computing for fast data streams and a batch computing behavior for massive workloads for delayed processing. While these two modes are clearly not new, lambda architectures allow them to coordinate their execution to avoid interference. However resource allocation over cloud infrastructure, has greatly impacted the overall performances (and importantly costs). If performance could be modeled in advance, architects could make better judgments on allocation of their resources to use the systems more efficiently. In this paper, we present a modeling approach, based on multiformalism and multisolution techniques, that provides a fast evaluation tool to support design choices about parameters and eventually lead to better architecture designs.

A performance modeling framework for lambda architecture based applications

Iacono, Mauro
;
2017

Abstract

The lambda architectural pattern allows to overcome some limitations of data processing frameworks. It builds on the methodology of having two different data processing streams on the same system: a real time computing for fast data streams and a batch computing behavior for massive workloads for delayed processing. While these two modes are clearly not new, lambda architectures allow them to coordinate their execution to avoid interference. However resource allocation over cloud infrastructure, has greatly impacted the overall performances (and importantly costs). If performance could be modeled in advance, architects could make better judgments on allocation of their resources to use the systems more efficiently. In this paper, we present a modeling approach, based on multiformalism and multisolution techniques, that provides a fast evaluation tool to support design choices about parameters and eventually lead to better architecture designs.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11591/385738
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