Large-scale web services are increasingly adopting the microservice architecture that mainly utilizes container technologies. Microservices are operated on complex configured infrastructures, such as containers, virtual machines, and physical machines. To ensure service quality of microservices, it is important to monitor not only the quality of services but also the quality of the infrastructures utilized by the services. Therefore, the metrics of the infrastructure related with the services should be traced. An extended Berkeley Packet Filter (eBPF) is a relatively new Linux's function, which is effectively used as a sensor of container-network metrics. There are two key challenges in realizing the service-linked monitoring system. One challenge is making the full-stack topology between microservices, containers, and machines visible to set the sensor related with the services. Another challenge is dynamic sensor management that can relocate the sensor quickly after the topology's change. In this paper, we propose a real-time monitoring system that creates a full-stack topology and relocates the sensor in conjunction with events from a container orchestrator. The system enables a dynamic deployment of the sensors related with the monitored services.

We demonstrate an oral scientific simulation and its visualization based on E-science. This oral scientific application will become an essential key component for medical and dental clinic in the near future because Bio-Medical simulations will provide a clinical index considering a prognostic of a disease. In this case, it was shown that the physical theory of sound production of speech sound, sibilant. However, it is difficult to acquire the computational and storage resources in the hospitals. Our E-science infrastructure enables scientists and clinicians to achieve the advanced information produced by simulations. As the result of this phase implementation for Bio-Medical simulation on E-science infrastructure, we could extract the scientific findings about the oral science. Moreover, this infrastructure can be used more generally because of the divided architecture between applications and E-science infrastructure.