Scalasca is a comprehensive open source performance analysis toolset for parallel programs, built with the aim of helping developers to identify opportunities for optimization. It covers all steps of performance analysis, from code instrumentation, measurement, and analysis to the visualization of the results. Scalasca can be used with parallel codes of any size, from multicore machines to the fastest supercomputers in the world. It supports MPI and/or OpenMP libraries. It supports Blue Gene, Cray XT and Linux clusters. Scalasca combines runtime summaries suitable to obtain a performance overview with in-depth studies of concurrent behavior via event tracing. The traces are analyzed to identify wait states that occur, for example, as a result of unevenly distributed workloads. The new version of Scalasca is based on the community instrumentation and measurement infrastructure Score-P. This improves interoperability with other performance analysis tools, by the use of the Open Trace Format 2 for event trace data, and CUBE4 for application profiles. CUBE is the interactive analysis report explorer GUI for Scalasca. Its color-coded scheme makes observation of timing phenomena straightforward. The talk will introduce the main components of Scalasca to the audience.