Model-Based Autonomic and Performance-Aware System Adaptation in Heterogeneous Resource Environments: A Case Study

Recent trends like cloud computing show that service providers increasingly adopt to modern self-adaptive system architectures promising higher resource efficiency and lower operating costs. In this paper, we apply a holistic model-based approach to engineering performance-aware system adaptation. More specifically, we employ the Descartes Modeling Language (DML), a domain-specific language for modeling the performance behavior and run-time adaptation processes of modern dynamic IT systems. The conducted case study evaluates the applicability and effectiveness of our approach and demonstrates that DML provides suitable modeling abstractions that can be used as a basis for self-adaptive performance and resource management in heterogeneous environments. We apply a holistic model-based approach to build a self-adaptive system that automatically maintains performance requirements and resource efficiency in the heterogeneous resource environment of Blue Yonder. The application of DML enables to automatically adapt service infrastructures to changing customer workloads and service-level agreements in heterogeneous environments.