DeDALO: Dependency Discovery and Analysis using On/off-line traffic measurement

Abstract

The welfare of our daily life depends, even more, on the correct functioning of complex distributed applications. Moreover, new paradigms such as Service oriented computing and Cloud computing encourage the design of application realized coupling services running on different nodes of the same data center or distributed in a geographic fashion. Dependencies discovery and analysis (DDA) is core for the identification of critical and strategical assets an application depends on, and it is valid support to risk and impact analysis. The goal of this research, framed in the context of the MOTIA 3 project, is to define methodologies and metrics to quantitatively and qualitatively evaluate service level dependencies in critical distributed systems. In literature there is a pletora of network monitoring tools, working at layer 2 and 3, that offer discovery dependencies features and that allow to building a dependency map of the observed system. On the contrary few works concentrate their attention on application level DDA. Often, DDA is used as a tool for distributed application management and typically gives a qualitative picture of system dependencies. At the best of our knowledge there are no examples of works oriented to application level dependency quantification that is, no indicators has been defined to quantify how much two services are dependent. This paper briefly describe DeDALO, the DEpendency Discovery and AnaLisys using Online traffic measurement framework we have designed and implemented