In order to enable automated IT management, i.e., considering management decisions based on entities from both technical (e.g., network management, virtual machine management) and non-technical domains (e.g., business processes, risk and cost management), a formal common reference model is required. We present a solution for the semantic information integration of different domain models in the context of automated IT management. For that, we formulate a core ontology based on the COBIT IT governance framework for integration on a conceptual level and discuss features of an extensible knowledge-based runtime system. We present a case study that integrates models from storage management, virtual machine management and a billing model and discuss the lessons learned from this IT management application.

Management of block storage virtualization systems in large environments can become very complex. For standard management tasks, such as the creation and maintenance of disk arrays, and problem isolation, specialized storage management tools are used. Such tools must query the storage virtualization system for topologies and performance statistics, correlating this information with external sources and defined policies, and providing an interface for the storage administrators. By using ontologies as information models in a storage management tool, correlation of elements, aggregation and querying becomes a lot more flexible and configurable. In this paper we present an ontology-based architecture that serves as backend for a storage management tool. We describe the approach and performance optimizations and give an evaluation of the prototypical implementation.

For enterprises, it is important to know how the IT infrastructure contributes to the business goals set. The COBIT IT governance framework provides a high-level view how this can be achieved. However, COBIT provides no machine-readable model that allows to refer to entities (processes, goals, actions, metrics etc.). In this paper, we present an approach to create a formal model for COBIT using an ontology. The COBIT ontology is enhanced with a formalization of metrics and a way to use selection rules and mappings to calculate metric values at runtime using data from existing systems. The calculated metric values are then inserted into the COBIT ontology and can be used for dynamic management decisions. The paper describes the modeling of the COBIT ontology and the corresponding runtime system.

IT Governance hat zum Ziel, dass die Unternehmens-IT die Strategie und Geschaftsziele des Unternehmens moglichst effizient unterstutzt. Um dies umzusetzen, existieren mehrere international anerkannte Verfahren und Standards wie z.B. COBIT, ITIL oder ISO 20000. Diese sind jedoch konzeptionell gehalten und machen meist keine Vorgaben zur technischen Umsetzung. Dieser Beitrag untersucht, wie mit Hilfe von Ontologien die Lucke zwischen solchen abstrakten Konzepten der Geschaftssicht und technisch erfassbaren Messwerten des IT-Monitorings geschlossen werden kann, konkret am Beispiel COBIT 5. Dies ermoglicht eine Top-Down-Sicht von Geschaftszielen uber Services bis hin zu den Komponenten der IT, die zur Erbringung der Ziele beitragen. Hierdurch wird die Transparenz (u.a. uber Kosten) erhoht. Auserdem ermoglicht eine solche Verbindung der Abstraktionsebenen eine Automatisierung der IT Governance sowie des IT Service Managements durch Regeln, die auf Konzepte der unterschiedlichen Ebenen Bezug nehmen konnen.

—Data stream mining (DSM) techniques can be used to extract knowledge from continuous data streams. In this paper, we present an approach providing a modelling and execution architecture for networks of DSM operators. It can be applied in resource-constrained environments, and provides capabilities for semantic enrichment of data streams. This allows processing of streams not only based on information contained in the streams, but also on their semantic contexts. The approach consists of a DSM runtime system, a concept for semantic tagging of stream elements, the integration of semantic information stores, and a domain-specific DSM network description language. A small ambient assisted living scenario is presented as an example application.

In the domain of IT management, numerous models, protocols and tools have been developed. To achieve the long-term goal of comprehensive, highly automated IT management, the various sources of information need to be combined. As syntactic translation is often not sufficient, ontologies can be used to unambiguously and comprehensively model IT environments including management rules. In this paper, we present an approach that combines the domain model, rules, instance data (which represents real-world systems) into an ontology. Moreover, probabilistic knowledge of the domain is modeled using Bayesian networks and integrated into the ontology. A runtime system that aggregates data and merges it into the ontology, and then uses a reasoner to evaluate management rules, is described as part of the approach of the ongoing project. Keywords-ontology; IT management; Bayesian network

This paper presents an approach for ontology-based IT management based on a heavyweight (formal) ontology using the Web Ontology Language (OWL). The ontology comprises a complete OWL representation of the Common Information Model (CIM) and management rules defined in the Semantic Web Rule Language (SWRL). The ontology not only models the managed system types, but a runtime system dynamically updates model instances in the ontology that reflect values of managed system entities. This allows the evalution of rules that take into account both model and model instances. A reaction module uses the CIM interface of the managed system to invoke CIM methods according to rule evaluation results, thus resulting in automated management. In order to ensure the consistency of the ontology when changes are performed, belief change theory is employed.

Today, an increasing number of enterprise applications are based on Service Oriented Architectures (SOA). The complexity of these applications requires Service Level Management (SLM) from the business process layer down to the actual implementation of application components. However, this complexity also hinders continuous application management, which relies on monitoring non-functional properties such as performance. A major challenge is to create a unified view on the overall system including (implementation level) performance across newly developed services and legacy components. In this paper, we present a comprehensive performance-aware application design method that can be applied to newly developed applications and legacy applications. The presented method is a result of the IT management project PerManEntA1.

Managing an IT environment requires the exchange of structured data between different agents. The Common Information Model (CIM) is a comprehensive open standard that specifies how managed elements in an IT environment are modelled as a set of common objects and relationships between them. It has however limited support for knowledge interoperability and aggregation, as well as reasoning. By converting the existing CIM model into a format that can be processed by semantic web tools, these limitations can be overcome. This paper describes how CIM can be converted into a Web Ontology Language (OWL) ontology including constructs for which no obvious direct conversion exists, such as CIM qualifiers.

Today, enterprise critical applications exhibit high complexity, and their non-functional properties like performance and availability are of major importance. From a user perspective, it is desirable to specify both functional and non-functional constraints on the business process model of an application system. The approach presented in this paper shows how business-level application monitoring can be performed based on implementation-level monitoring records. To achieve this, a mapping between application workflow models and an existing instrumentation is defined. This way, monitoring records, which are generated at application runtime, can be related to the workflow model. Our system uses this mapping and a stream of monitoring records to evaluate previously modelled performance constraints and to trigger reactions on constraint violations.

This thesis presents an approach that deals with the ever-growing amount of data in knowledge bases, especially concerning knowledge interoperability and formal representation of domain knowledge. There arc multiple issues that must be addressed with current systems. A multitude of different formats, sources and tools exist in a domain, and it is desirable to develop their use further towards a standardised environment. Such an environment should support both the representation and processing of data from this domain, and the connection to other domains, where necessary. In order to manage large amounts of data, it should be possible to perform whatever actions that need to be performed on the data automatically. This requires that the domain model and actual data that is modelled by it are available in a formal, comprehensive and machine-readable format. The definition of rules must be possible as well. Management of an IT environment is examined as an example domain. Semantic Web technology delivers the base on which the solution to the aforementioned problems can be built. The solution approach presented in this thesis is based on an Web Ontology Language (OWL) ontology, which combines a domain model, instance data and rules. For the particular domain of IT management, the Common Information Model (CIM) is employed and converted into an OWL ontology. A runtime system that has capabilities for importing updated information about the managed system is developed. Current information is extracted using a CIM client module and added as instance data to the ontology. An external reasoner that is part of the runtime system is used to evaluate the information in the ontology, including the rules. Through the combination of domain data, rules that make use of structural and dynamically updated information can be built. Using the evaluation results, reactions can be triggered based on this combined information.