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Software rarely comes without maintenance after it is released. There can be bugs not captured in development or performance that might not meet expectations; therefore, it is crucial to be able to collect data from running software, preemptively addressing such issues. A common way to monitor the general health of a system is by monitoring it through the users' perspective — so-called "black-box" monitoring. Making a more sophisticated analysis of software requires code that offers no functionality to the software, whose purpose is to create data about the software itself. A common way of creating such data is through logging. While logging can be used in the general case, alternatively, more specific solutions can offer an easier pipeline to work with; while not being suited for tasks such as root-cause analysis.This study briefly looks at four different frameworks, all having different approaches to collect and structure data. This study also covers the development of a proof-of-concept framework that creates structured events through logging — along with a SQL-server database to store the event data.

Les agents mobiles peuvent physiquement migrer à travers un réseau informatique dans le but d’effectuer des tâches sur des machines, ayant la capacité de leur fournir un support d’exécution. Ces agents sont considérés comme composants autonomes, une propriété qui leur permet de s'adapter à des environnements dynamiques à l'échelle d'un réseau large. Ils peuvent également échanger des informations entre eux afin de collaborer au sein de leur groupe, nous parlerons ainsi d'une communauté d'agents mobiles. Nous avons développé ce concept de communauté, en se référant aux recherches et aux études précédentes pour définir un nouveau modèle comportemental d'agent mobile. Ce modèle est utilisé pour répondre aux besoins de la surveillance logicielle. Celle ci consiste à collecter des événements à partir de plusieurs sources de données (Log, événements système…) en vue de leur analyse pour pouvoir détecter des événements anormaux. Cette démarche de surveillance s'appuie sur plusieurs types d'agents mobiles issus du même modèle. Chaque type d'agent gère un domaine fonctionnel précis. L'ensemble des ces agents constitue une communauté pouvant collaborer avec différentes autres communautés lorsqu'il existe plusieurs sites à surveiller. Les résultats de cette approche nous ont permis d'évoquer les limites liées à la taille des données collectées, ce qui nous amène à de nouvelles perspectives de recherche et à penser un agent mobile "idéal". Enfin, nous nous intéressons également à l'application de la communauté d'agent mobile pour les systèmes de détection d'intrusion et la remontée d'anomalie / Mobile agents can physically travel across a network, and perform tasks on machines, that provide agent hosting capability. These agents are autonomous; this property allows them to adapt themselves on a dynamic environment in a large network. Also, they can exchange information and data in order to collaborate within their group; in this case we can talk about community of mobile agents. We refer to previous studies and research to develop this concept of community by defining a new behavioural pattern of mobile agent. This pattern is used in monitoring software approach which consist of collecting events from various data sources (log file, OS events…) and analyse them to detect abnormal events. This approach is based on different kind of mobile agents, each kind manages some features. Whole of those mobile agents constitute a community which collaborate with other communities if there are a several sites to supervise. The results of this approach allow us to evoke some limits related to size of collected data. This limit pushes us to have a new possibility of research and probably define an ideal mobile agent. Lastly, we illustrate our mobile approach with results about intrusion detection system application to retrieve anomalies

This degree project deals with license management for EBITool. It´s about providing protection and monitoring for a Java Application via a license server, and the construction of it. An analysis that discusses the approach and other possible courses of action is also included. Additionally, it covers a discussion of a prototype implementation of the model solution from the analysis. The prototype is a Java EE application that deploys to JBoss AS7. It´s developed using the JBoss Developer Studio 5.0.0, an Eclipse IDE with JBoss Tools preinstalled. It exposes web services to Java Applications through SOAP via JAX-WS. Using Hibernate, the web service Enterprise Java Beans get access to a PostgreSQL 9.1 database via entity classes mapped to the database through the Java Persistence API.