A. Corso Radu

The Electronic Logbook for the Information Storage of ATLAS Experiment at LHC (ELisA)

A large experiment like ATLAS at LHC (CERN), with over three thousand members and a shift crew of 15 people running the experiment 24/7, needs an easy and reliable tool to gather all the information concerning the experiment development, installation, deployment and exploitation over its lifetime. With the increasing number of users and the accumulation of stored information since the experiment start-up, the electronic logbook actually in use, ATLOG, started to show its limitations in terms of speed and usability. Its monolithic architecture makes the maintenance and implementation of new functionality a hard-to-almost-impossible process. A new tool ELisA has been developed to replace the existing ATLOG. It is based on modern web technologies: the Spring framework using a Model-View-Controller architecture was chosen, thus helping building flexible and easy to maintain applications. The new tool implements all features of the old electronic logbook with increased performance and better graphics: it uses the same database back-end for portability reasons. In addition, several new requirements have been accommodated which could not be implemented in ATLOG. This paper describes the architecture, implementation and performance of ELisA, with particular emphasis on the choices that allowed having a scalable and very fast system and on the aspects that could be re-used in different contexts to build a similar application.

Applications of advanced data analysis and expert system technologies in the ATLAS Trigger-DAQ Controls framework

The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment is a very complex distributed computing system, composed of more than 20000 applications running on more than 2000 computers. The TDAQ Controls system has to guarantee the smooth and synchronous operations of all the TDAQ components and has to provide the means to minimize the downtime of the system caused by runtime failures. During data taking runs, streams of information messages sent or published by running applications are the main sources of knowledge about correctness of running operations. The huge flow of operational monitoring data produced is constantly monitored by experts in order to detect problems or misbehaviours. Given the scale of the system and the rates of data to be analyzed, the automation of the system functionality in the areas of operational monitoring, system verification, error detection and recovery is a strong requirement. To accomplish its objective, the Controls system includes some high-level components which are based on advanced software technologies, namely the rule-based Expert System and the Complex Event Processing engines. The chosen techniques allow to formalize, store and reuse the knowledge of experts and thus to assist the shifters in the ATLAS control room during the data-taking activities.