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Recent technological advances have enabled the deployment of wide area applications against Internet accessible sources. A performance challenge to applications in such a setting is the unpredictable end-to-end latency of accessing these sources. We use passive information gathering mechanisms to learn end-to-end latency distributions and construct latency profiles (LPs). We hypothesize that a group of clients, within an autonomous system (AS), that are accessing a content server, in another AS, may be represented by (one or more) LPs. Related networking research on IDMaps, points of congestion, and BGP routes support such hypothesis. We develop aggregate LPs to provide coverage of groups (clusters) of client-server pairs. Using data gathered from a (limited) experiment we demonstrate the feasibility of constructing LPs.