The Software Defined Networking (SDN) paradigm enables quick deployment of software controlled network infrastructures, however new approaches to system monitoring are required to provide network administrators with instant feedback on a network's health. This paper details the deployment of an SDN system architecture featuring the integration of a cloud-based, real-time log-analysis platform. The proposed architecture uses log data collected from host machines, OpenFlow switches and the SDN controllers in a non-invasive style. This work uses a commercially available correlation platform to provide network administrators with a real-time view of the network status and the approach is validated under two scenarios:network overload and a security attack.

Understanding system utilization is currently a difficult challenge for industry. Current monitoring tools tend to focus on monitoring critical servers and databases within a narrow technical context, and have not been designed to to manage extremely heterogeneous IT infrastructure such as desktops, laptops, and servers, where the number of devices can be in the order of tens of thousands. This is an issue for many different domains (organizations with large IT infrastructures, cloud computing providers, or software as a service providers) where an understanding of how computer hardware is being utilized is essential for understanding business cost, workload migrations and future investment requirements. Furthermore, organizations find it difficult to understand the raw metrics collected by current monitoring tools, in particular when trying to understand to what degree their systems are being utilized in the context of different business purposes. This paper presents different techniques for the extraction of meaningful resource utilization information from raw monitoring data, a utilization scoring algorithm, and then subsequently outlines a profile-based method for tracking the utilization of IT assets (systems) in large heterogeneous IT environments. We intend to determine how efficiently system resources are utilized considering their business use. We will provide to the end-user an assessment of the system utilization together with additional information to perform remedial action.

Monitoring, analysing and understanding component based enterprise software systems are challenging tasks. These tasks are essential in solving and preventing performance and quality problems. Obtaining component level interactions which show the relationships between different software entities is a necessary prerequisite for such efforts. This paper focuses on component based Java applications, currently widely used by industry. They pose specific challenges while raising interesting opportunities for component level interaction extraction tools. We present a range of representative approaches for dynamically obtaining and using component interactions. For each approach we detail the needs it addresses, and the technical requirements for building an implementation of the approach. We also take a critical look at the different available implementations of the various techniques presented. We give performance and functional considerations and contrast them against each other by outlining their relative advantages and disadvantages. Based on this data, developers and system integrators can better understand the current state-of-the-art and the implications of choosing or implementing different dynamic interaction extraction techniques.