Waldvogel, Claudio (2015) Specification and Runtime Extraction of Enterprise Application Architectures for Expert-Guided Performance Problem Diagnosis. (Master thesis), University of Stuttgart, Stuttgart, Germany, 103 pp.

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Abstract

The non-functional requirements (NFRs) of enterprise application systems
(EASs) have a significant impact on the Key Performance Indicators
(KPIs) of companies. Among NFRs like accessibility, security, and
reusability is performance considered as one of the top most important.
Performance quantifies the degree to which an application meets the
requirements, with respect to response times and resource utilization.
To enable early performance problem detection, so-called Application
Performance Management (APM) tools are integrated in an EAS life cycle.

Due to the high initial and ongoing configuration effort of APM tools,
they have hardly been accepted in the industry. This results in
time-consuming and error-prone manual performance problem diagnosis.
These vulnerabilities of APM tools are addressed by the diagnoseIT
research project. The main objective of the project is to enrich
existing APM processes with automated configuration of instrumentations
as well as automated performance problem detection and diagnosis. Since
there is already a wide variety of APM tools, diagnoseIT does not
implement a new tool to measure performance metrics. Instead, already
existing APM tools provide their monitoring data to diagnoseIT. As part
of this research project arose this work and contributed three
components to the diagnoseIT framework.

As a basis for performance problem diagnosis, diagnoseIT needs to know
a variety of information (e.g., system architecture, execution
environment, and dynamic runtime data) about the monitored EAS.
Therefore, an Enterprise Performance Model (EPM) was designed and
implemented in the first part of this thesis. The second part of the
work was to provide a maintenance service for the EPM and an associated
integration interface for third-party APM tools. The implemented
components were assembled to a prototypical implementation of the
diagnoseIT framework. The final evaluation of the implemented solution
has shown that we are able to maintain the EPM by connecting the Kieker
application performance monitoring tool to diagnoseIT. The evaluation
results of extensive load tests showed, however, that the processable
amount of data is limited by the current implementation of the
persistence unit.

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