Container Mapping and its Impact on Performance in Containerized Cloud Environments

The past few years have witnessed many software companies refactoring their monolithic applications into microservices to take advantage of containers in Cloud-native and DevOps-driven environments. Modern Cloud environments achieve high levels of scalability, flexibility, availability and business agility by combining two different kinds of virtualization: virtual machines and containers. The deployment of complex applications in such environments should be done by taking into account the interactions that may arise from the overlapping of these two different levels of virtualization. In this paper, we first describe a preliminary evaluation of a containerized application that has been obtained by refactoring a monolithic application into microservices. The application was deployed in a private Cloud system that relies on Kubernetes, which is a cluster management software for Docker containers that have been deployed on top of OpenStack-managed KVM virtual machines. Subsequently, in order to systematically investigate the possible interactions that can be produced when multiple containers running different kinds of workloads are activated on top of virtual machines, we present and analyze the results obtained by running different benchmarks in a testbed setup. From the analysis of the benchmark results, we derive some guidelines that should be taken into account by container schedulers when container orchestration platforms, such as Kubernetes, are deployed on top of a virtualized IaaS layer.