As we move from 5G to 6G, edge computing is one of the concepts that needs revisiting. Its core idea is still intriguing: Instead of sending all data and tasks from an end user's device to the cloud, edge servers deployed in close proximity to the user serve as proxy for the cloud. This is particularly interesting for upcoming machine learning (ML)-based intelligent services, which require substantial computational and networking performance for continuous model training. At the same time, disruptions and major outages of our communication infrastructure pose a very realistic thread to our mission-critical infrastructure and may also severely impact our daily life. Lessons learned from previous natural disasters helped identifying problems but also solution spaces. In this talk, we discuss a way forward, namely the virtual edge computing (V-Edge) concept. V-Edge helps bridging the gap between cloud, edge, and fog by virtualizing all available resources including the end users' devices and making these resources widely available. Thus, V-Edge acts as an enabler for novel microservices as well as cooperative computing solutions in next-generation networks. We introduce the general V-Edge architecture, and we characterize some of the key research challenges to overcome, to enable wide-spread and intelligent edge services. This is further supported by concepts of turning mobile systems such as cars and trucks of first responders into mobile base stations to provide network coverage even when infrastructure such as the energy grid or the 5G base stations are down.