Modern organizations increasingly deploy applications across the so-called Edge-Cloudcontinuum. Such deployment requires a high degree of human intervention. Furthermore, themanagement of applications during runtime also requires heavy configuration. To automatethis process, there are today several tools that manage (orchestrate) the deployment andrunning of applications. Still, with the increasing trend to bring applications, services, andprocesses closer to data sources (far Edge), there is a growing need to have an efficient andflexible orchestration of resources from the far Edge to Cloud. This white paper provides an overview and a comparative analysis of cognitive and intelligentresource management techniques for the Edge-Cloud continuum, which are developed in sixEuropean research and innovation projects: CODECO, COGNIFOG, COGNIT, MLSysOps,ENACT, and DECICE. These projects address the growing complexity of managing distributedcomputing resources across Cloud and Edge environments. In this direction they developadvanced AI-driven approaches to optimizing performance, scalability, and security. The document emphasizes the role of cognitive techniques, such as Machine Learning (ML)and Artificial Intelligence (AI), in automating resource allocation, workload distribution, andsystem adaptation in real-time. These technologies are essential for managing heterogeneousenvironments that span from IoT devices at the Edge to centralized Cloud data centres.Key challenges in this domain include ensuring reliable network connectivity, protecting dataprivacy, managing heterogeneous resources, and scaling deployments efficiently. Each of theprojects discussed in this paper offers a unique approach and solution to these challenges.