Instrumentation with Runtime Monitors for Extraction of Performance Models during Software Evolution: Unterschied zwischen den Versionen
(Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Florian Fei |email=uhevm@student.kit.edu |vortragstyp=Bachelorarbeit |betreuer=Emre Taşpolatoğlu |termin=Institutsseminar/2019-09-06…“) |
|||
| Zeile 5: | Zeile 5: | ||
|betreuer=Emre Taşpolatoğlu | |betreuer=Emre Taşpolatoğlu | ||
|termin=Institutsseminar/2019-09-06 | |termin=Institutsseminar/2019-09-06 | ||
| − | |kurzfassung= | + | |kurzfassung=In recent times, companies are increasingly looking to migrate their legacy software system |
| + | to a microservice architecture. This large-scale refactor is often motivated by concerns over | ||
| + | high levels of interdependency, developer productivity problems and unknown boundaries | ||
| + | for functionality. However, modernizing legacy software systems has proven to be a | ||
| + | di�cult and complex process to execute properly. This thesis intends to provide a mean | ||
| + | of decision support for this migration process in the form of an accurate and meaningful | ||
| + | performance monitoring instrumentation and a performance model of said system. It | ||
| + | speci�cally presents an instrumentation concept that incurs minimal performance overhead and is generally compatible with legacy systems implemented using object-oriented | ||
| + | programming paradigms. In addition, the concept illustrates the extraction of performance | ||
| + | model speci�cs with the monitoring data. This concept was developed on an enterprise | ||
| + | legacy system provided by Capgemini. This concept was then implemented on this system. | ||
| + | A subsequent case study was conducted to evaluate the quality of the concept. | ||
}} | }} | ||
Version vom 2. September 2019, 08:53 Uhr
| Vortragende(r) | Florian Fei | |
|---|---|---|
| Vortragstyp | Bachelorarbeit | |
| Betreuer(in) | Emre Taşpolatoğlu | |
| Termin | Fr 6. September 2019 | |
| Vortragsmodus | ||
| Kurzfassung | In recent times, companies are increasingly looking to migrate their legacy software system
to a microservice architecture. This large-scale refactor is often motivated by concerns over high levels of interdependency, developer productivity problems and unknown boundaries for functionality. However, modernizing legacy software systems has proven to be a di�cult and complex process to execute properly. This thesis intends to provide a mean of decision support for this migration process in the form of an accurate and meaningful performance monitoring instrumentation and a performance model of said system. It speci�cally presents an instrumentation concept that incurs minimal performance overhead and is generally compatible with legacy systems implemented using object-oriented programming paradigms. In addition, the concept illustrates the extraction of performance model speci�cs with the monitoring data. This concept was developed on an enterprise legacy system provided by Capgemini. This concept was then implemented on this system. A subsequent case study was conducted to evaluate the quality of the concept. | |