During the reporting period, MultiXscale made significant strides in automating data collection for performance and scalability measurements of key software packages. As part of its ongoing activities, MultiXscale has consistently employed a testing framework, based on ReFrame, to conduct performance and scalability tests for production releases of essential applications. This testing suite is operational for selected applications on EuroHPC systems Karolina and Vega, forming an integral part of collaboration efforts with CASTIEL2 in Continuous Integration (CI). Efforts were also directed towards establishing a central stack of scientific software and their dependencies, representing a crucial advancement towards achieving measurable outcomes. This shared software stack, already deployed on EuroHPC JU systems Vega and Karolina by the end of the first reporting period, serves as the foundation for a CI infrastructure aimed at expediting application development. Notably, key software packages such as ALL, ESPResSo, LAMMPS, and OpenFOAM, along with their requisite dependencies, are already accessible in the production version of this shared software stack, with plans underway to incorporate additional packages like waLBerla. To enhance automation further, a GitHub Action was developed to utilize the shared software stack for automated testing of software under development via the GitHub platform. Discussions and planning are actively underway, in collaboration with CASTIEL2, to extend this shared software stack to other EuroHPC JU systems and to establish a comprehensive CI infrastructure for the broader EuroHPC ecosystem. Designed to be compatible with various Linux operating systems, the shared software stack is effectively streamed to client systems (and one could draw parallels with streaming media platforms). With the shared software stack already encompassing 500 different software installations for each supported CPU target by the end of the first reporting period, including vital packages pertinent to MultiXscale, comprehensive user-facing documentation has been provided. Additionally, a support policy and semi-automated workflow for adding software have been implemented, ensuring accessibility and ease of use for stakeholders. Initial support for software capable of running on NVIDIA GPUs has also been initiated, further broadening the capabilities of the shared software stack.