Documented IT Assets form the foundation of most tasks and processes in IT management, e.g. risk management, IT architecture planning, change management and incident management. In practice, IT assets are often documented in Enterprise Architecture Management (EAM) tools or Configuration Management Databases (CMDBs). These assets are documented on several layers, from infrastructure to application and finally business, alongside their dependencies to each other.
Current EAM tools and CMDBs are not capable to fulfill the requirements of a new generation of IT systems. These form networks of interconnected, rapidly changing assets, and emerge in scenarios like Smart Grids, Industry 4.0 or in the operation of container-based Cloud Services. Studies conducted in recent years proof that user of EAM tools rate documentation as out-dated, incomplete, inconsistent or of inadequate granularity.
This project is part of our long-standing activities to research the root causes for these quality issues and to develop new, cost-effective methods and tools in order to increase the quality of IT asset documentation.
Within the project we focus on a widely neglected aspect, which is the connection of IT asset models with information extracted from external data sources, for example runtime environments. Our aim is to make a significant step forward to situation-aware knowledge bases that help IT managers and architects in making informed decisions. To achieve this goal, two key challenges must be adressed.
On the one hand, these are functional requirements that concern questions revolving around finding suitable data sources, visualization types and propagation rules for metrics. On the other hand, we need to face a number of difficult challenges regarding the model repository, for example the configuration for metrics, high-performance persistence and querying and data versioning. Within the project, we conduct both empirical studies with experts from industry and develop a generic repository prototype. The results will be evaluated in two case studies in the context of Green IT and Security Risks.
Univ. Prof. Dr. Ruth Breu
Dr. Matthias Farwick
Martin Häusler, MSc.
Mag. Emmanuel Nowakowski, MSc.
Technikerstraße 21a, University of Innsbruck, Austria