Virtualización del sistema operativo FreeBSD sobre Xen

El sistema operativo FreeBSD soporta distintos modos de virtualización sobre la plataforma Xen. Cada uno usa una técnicas de virtualización distinta, logrando mayor o menor integración con el hipervisor. Actualmente, están soportados en FreeBSD el modo paravirtualizado, virtualizado asistido por hardware y modos híbridos. Este trabajo consiste fundamentalmente en un estudio práctico de los distintos modos de virtualización Xen soportados en FreeBSD, basándose en pruebas de sintéticas de rendimiento. Se incluye una comparativa con gráficas de los resultados obtenidos mediante un sistema de pruebas automáticas desarrollado en shell script y R. ABSTRACT. The FreeBSD operative system supports several virtualization modes when used over the Xen platform. Each mode uses a different virtualization technique, achieving different level of integration with the hypervisor. Current supported modes on FreeBSD are paravirtualized mode, hardware virtualization assisted and hybrid modes. This work is a survey on FreeBSD virtualization over Xen, focused on performance by benchmark testing all supported virtual machine implementations. The study includes a comparative of the measured test results performed by an automatic testing tool developed on shell and R script

Autonomic Performance-Aware Resource Management in Dynamic IT Service Infrastructures

Model-based techniques are a powerful approach to engineering autonomic and self-adaptive systems. This thesis presents a model-based approach for proactive and autonomic performance-aware resource management in dynamic IT infrastructures. Core of the approach is an architecture-level modeling language to describe performance and resource management related aspects in such environments. With this approach, it is possible to autonomically find suitable system configurations at the model level

Architecture-Level Software Performance Models for Online Performance Prediction

Proactive performance and resource management of modern IT infrastructures requires the ability to predict at run-time, how the performance of running services would be affected if the workload or the system changes. In this thesis, modeling and prediction facilities that enable online performance prediction during system operation are presented. Analyses about the impact of reconfigurations and workload trends can be conducted on the model level, without executing expensive performance tests

Performance Isolation in Multi-Tenant Applications

The thesis presents methods to isolate different tenants, sharing one application instance, with regards to he performance they observe. Therefore, a request based admission control is introduced. Furthermore, the publication presents methods and novel metrics to evaluate the degree of isolation a system achieves. These insights are used to evaluate the developed isolation methods, resulting in recommendations of methods for various scenarios