Supporting Predictive Change Impact Analysis: A Control Call Graph Based Technique
APSEC '05 Proceedings of the 12th Asia-Pacific Software Engineering Conference
Integrating Influence Mechanisms into Impact Analysis for Increased Precision
ICSM '06 Proceedings of the 22nd IEEE International Conference on Software Maintenance
Precise Dynamic Impact Analysis with Dependency Analysis for Object-oriented Programs
SERA '07 Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications
Evolution of storage management: transforming raw data into information
IBM Journal of Research and Development
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The complexity of modern data centers has evolved significantly in recent years. One typically is comprised of a large number and types of middleware and applications that are hosted in a heterogeneous pool of both physical and virtual servers, connected by a complex web of virtual and physical networks. Therefore, to manage everything in a data center, system administrators usually need a plethora of management tools since one tool often manages only one type of devices. The boundaries between the different management tools can limit productivity of system administrators on their daily tasks as each tool only offers a partial view of the entire managed environment. As a result, advanced analytics such as impact analysis and problem determination are generally not achievable using the traditional management tools as they require a holistic view of the entire data center. In this paper, we describe an integrated management system for applications, servers, network and storage devices called DataGraph. Our system integrates data across heterogeneous point products and agents for management and monitoring to enable the above mentioned management analytics capabilities. A common data model is introduced to federate data collected by the different tools in multiple database repositories so no modifications are needed to existing management tools. A common integrated web user interface is implemented to facilitate management tasks that would otherwise require invoking multiple tools. We deployed this tool in a lab environment and demonstrated these analytics capabilities through several case studies.