1. A method comprising: creating one or more context insight records representing an indication of a behavior of a service based on raw footprint data related to use of said service by a population of users; selecting at least one anomaly criteria dimension; defining possible values for multiple dimensions of said one or more context insight records in response to a result of a scanning of said one or more context insight records; analyzing, by an analyzer that is a hardware component, said one or more context insight records, in response to said at least one anomaly criteria dimension and to at least one of said possible values defined; detecting based on said analyzing a dynamically defined anomaly of said service by generating a first generation of candidate anomalies by segmenting said one or more context insight records along a segmentation dimension of said raw footprint data; generating a consecutive generation of candidate anomalies by modifying, adding or deleting one or more candidate anomalies of said first generation; said consecutive generation of candidate anomalies further comprising: modifying said first generation into said consecutive generation by activating a dimension of said one or more context insight records; selecting, by the hardware analyzing, at least one of each types of dimensions of said context insight records said dimensions comprising: criteria, segmenting, and testing dimensions; wherein said criteria dimensions represent characteristics of at least one context insight record population; wherein said segmenting dimensions divide said at least one context insight record population into several sub-populations; wherein said testing dimensions comprise criteria by which different sub-populations of the segmenting dimensions are tested; wherein the generating of at least one of the generations of candidate anomalies is response to, said criteria, segmenting and said testing dimensions selected by the hardware analyzer; repeating generating consecutive generations of candidate anomalies until a convergence condition holds true; and assisting in resolving a problem in the service in response to the dynamically defined anomaly.