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Distributed digital infrastructures for computation and analytics are now evolving towards an interconnected ecosystem allowing complex applications to be executed from IoT Edge devices to the HPC Cloud (aka the Computing Continuum, the Digital Continuum, or the Transcontinuum). Understanding endto-end performance in such a complex continuum is challenging. This breaks down to reconciling many, typically contradicting application requirements and constraints with low-level infrastructure design choices. One important challenge is to accurately reproduce relevant behaviors of a given application workflow and representative settings of the physical infrastructure underlying this complex continuum. In this paper we introduce a rigorous methodology for such a process and validate it through E2Clab. It is the first platform to support the complete analysis cycle of an application on the Computing Continuum: (i) the configuration of the experimental environment, libraries and frameworks; (ii) the mapping between the application parts and machines on the Edge, Fog and Cloud; (iii) the deployment of the application on the infrastructure; (iv) the automated execution; and (v) the gathering of experiment metrics. We illustrate its usage with a real-life application deployed on the Grid'5000 testbed, showing that our framework allows one to understand and improve performance, by correlating it to the parameter settings, the resource usage and the specifics of the underlying infrastructure.

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