  Edge-to-cloud computing is an emerging paradigm for distributing
computational tasks between edge devices and cloud resources. Different
approaches for orchestration, offloading, and many more purposes have been
introduced in research. However, it is still not clear what has been
implemented in the industry. This work aims to merge this gap by mapping the
existing knowledge on edge-to-cloud tools by providing an overview of the
current state of research in this area and identifying research gaps and
challenges. For this purpose, we conducted a Multivocal Literature Review (MLR)
by analyzing 40 tools from 1073 primary studies (220 PS from the white
literature and 853 PS from the gray literature). We categorized the tools based
on their characteristics and targeted environments. Overall, this systematic
mapping study provides a comprehensive overview of edge-to-cloud tools and
highlights several opportunities for researchers and practitioners for future
research in this area.
