We consider the problem of diagnosing performance problems in distributed system and networks given end-to-end performance measurements provided by test transactions, or probes. Common techniques for problem diagnosis such as, for example, codebook and network tomography usually assume a known dependency (e.g., routing) matrix that describes how each probe depends on the systems components. However, collecting full information about routing and/or probe dependencies on all systems components can be very costly, if not impossible, in large-scale, dynamic networks and distributed systems. We propose an approach to problem diagnosis and dependency discovery from end-to-end performance measurements in cases when the dependency/routing information is unknown or partially known. Our method is based on Blind Source Separation (BSS) approach that aims at reconstructing unobserved input signals and the mixing-weights matrix from the observed mixtures of signals. Particularly, we apply sparse n...