Textual Modeling for Cloud-Native Performance Simulation
| Typ | Bachelorarbeit oder Masterarbeit | |
|---|---|---|
| Aushang | ||
| Betreuer | Wenden Sie sich bei Interesse oder Fragen bitte an: Maximilian Hummel (E-Mail: maximilian.hummel@kit.edu) |
Motivation
Text-based modeling streamlines architecture model creation, but its grammar and abstractions are rooted in classic Palladio concepts. Modern cloud-native architectures with containers, services, and Kubernetes workflows don’t map cleanly to this world. Moreover, there is a lack of accessible, YAML-like input for DevOps engineers and architects used to declarative configs. Bridging this gap will make performance simulation more accessible usable in cloud-native contexts.
Tasks
The goal of this thesis is to extend the existing text-based modeling language with support for cloud-native concepts and a simplified, YAML-inspired syntax. Key steps include:
- Analyzing and extending the current TPCM/Xtext grammar to cover typical cloud-native patterns.
- Enabling concise, user-friendly modeling inspired by real-world configuration files (e.g., Kubernetes YAML).
- Implementing a mapping layer from the extended language to PCM models for use with Palladio and Simulizer.
You’ll gain skills in DSL engineering, model transformation, and the intersection of architecture modeling and cloud-native deployment.
Additional Info
Supervision in German or English.
Contact: [maximilian.hummel@kit.edu](mailto:maximilian.hummel@kit.edu)