The rapid evolution of edge computing, has enabled the deployment of latency-sensitive applications at the network edge. This paradigm is essential for real-time processing scenarios, such as autonomous driving, unmanned aerial vehicles (UAVs), and computer vision applications, where deploying at the edge is not just advantageous but necessary to meet the strict latency and reliability requirements. These applications leverage distributed microservices (MSs) architectures, enabling scalability, fault tolerance, and efficient resource utilization while ensuring resilience and minimizing communication delays with the client. However, the distributed nature of MS architectures introduces challenges in efficient coordination and data sharing. Additionally, to fully exploit the benefits of edge computing, effective management and dynamic relocation of MSs are essential for maintaining service efficiency and responsiveness.