Enabling zero-touch cloud edge computing continuum management

Automating the Life-Cycle Management of Cloud Edge Computing Continuum (CECC) is crucial to unlocking the full potential of emerging use cases. By providing a spectrum wherein applications can seamlessly run and migrate across various locations, manual operations (placement, scaling, migration of applications) become obsolete as they fail to achieve optimal resource allocation and performance efficiency. This thesis represents incremental progress towards the paradigm of zero-touch CECC management. First, we propose an end-to-end multi-domain service monitoring framework. Then, we conduct an experimental study to profile and explore the behavior of different types of applications in cloud-native environments. Afterwards, we employ machine learning and XAI techniques to build models capable of predicting and correcting performance degradation in applications. Finally, we propose an architecture for the LCM of CECC applications, leveraging application profiles. EN-US">