In the last decade, novel software architectural patterns, such as microservices, have emerged to improve application modularity and to streamline their development, testing, scaling, and component replacement. To support these new trends, new practices as DevOps methodologies and tools, promoting better cooperation between software development and operations teams, have emerged to support automation and monitoring throughout the whole software construction lifecycle. That affected positively several IT companies, but also helped the transition to the softwarization of complex telco infrastructures in the last years. Container-based technologies played a crucial role by enabling microservice fast deployment and their scalability at low overhead; however, modern container-based applications may easily consist of hundreds of microservices services with complex interdependencies and call for advanced orchestration capabilities. While there are several emerging container orchestration engines, such as Docker Swarm, Kubernetes, Apache Mesos, and Cattle, a thorough functional and performance assessment to help IT managers in the selection of the most appropriate orchestration solution is still missing. This paper aims to fill that gap. Collected experimental results show that Kubernetes outperforms its counterparts for very complex application deployments, while other engines can be a better choice for simpler deployments.