These are our research projects in the field of performance management which are currently in progress.
SPEC DevOps Performance Working Group
As a founding member of the SPEC DevOps Performance Working Group, fortiss contributes to research by integrating activities of system development (Dev) and IT operations (Ops) with regards to performance of application systems. Further members are Kiel University, Karlsruhe Institute of Technology, NovaTec GmbH, University of Stuttgart and University of Würzburg.
fortiss and Dynatrace research cooperation
fortiss cooperates with Dynatrace, one of the leading Application Performance Management (APM) software providers. The scope of this cooperation is to combine the PMW-Tools performance model generator with the dynaTrace APM solution. The automatic performance model generation based on APM data helps to better support PMW activities such as capacity planning.
Performance evaluation of in-memory and traditional relational databases
Performance analysis and comparison of two SAP deployments of which one uses Microsoft SQL Server and one SAP HANA. The analysis comprises measuring execution times of several time-critical reports as well as monitoring response time behavior of user interface elements. Within the framework of the project, a migration between the two SAP deployments is accomplished.
Technology benchmark in big data
As part of a technology benchmark in big data, a case study of state-of-the-art analytics architectures with reference to their performance is conducted. Analytics architectures describe how to store and access data and how to apply methods for analyzing this data. Trends like architectures for massive parallel processing are discussed and leading research groups for several topics are identified.
Performance analysis of smart grid architectures
Modeling of architectures for advanced metering infrastructures and smart grid systems which have to manage several hundreds of thousands of smart meter devices. Therefore, design alternatives with regards to performance, scalability and reliability are evaluated and required hardware capacities are predicted.
Performance evaluation of a big data system
Analysis of functional and non-functional requirements of a big data system and assistance in conducting a proof of concept for different scenarios. In particular, performance measurements for several common analytical use cases are conducted as well as measurements to examine scalability in case of increasing system size and/or data volume.