ECLYPSE: A Python Framework for Simulation and Emulation of the Cloud‐Edge Continuum

The Cloud-Edge continuum enhances application performance by bringing computation closer to data sources. However, it presents considerable challenges in managing resources and determining application service placement, as these tasks require analyzing diverse, dynamic environments characterized by fluctuating network conditions. Addressing these challenges calls for tools combining simulation and emulation of Cloud-Edge systems to rigorously assess novel application and resource management strategies. In this paper, we introduce ECLYPSE, a Python-based framework that enables the simulation and emulation of the Cloud-Edge continuum via adaptable resource allocation and service placement models. ECLYPSE features an event-driven architecture for dynamically adapting network configurations and resources. It also supports seamless transitions between simulated and emulated setups, thus enabling the execution of experiments in simulated, emulated, and hybrid settings. In this work, we illustrate and assess ECLYPSE capabilities over three use cases, demonstrating the framework's effectiveness in rapid prototyping across diverse scenarios.