Abstract
The Trigger and Data Acquisition (TDAQ) system of the ATLAS detector at the Large Hadron Collider at CERN is composed of a large number of distributed hardware and software components (about 3000 computers and more than 25000 applications) which, in a coordinated manner, provide the data-taking functionality of the overall system. During data taking runs, a huge flow of operational data is produced in order to constantly monitor the system and allow proper detection of anomalies or misbehaviours. In the ATLAS trigger and data acquisition system, operational data are archived and made available to applications by the P-BEAST (Persistent Back-End for the Atlas Information System of TDAQ) service, implementing a custom time-series database. The possibility to efficiently visualize both realtime and historical operational data is a great asset facilitating both online identification of problems and post-mortem analysis. This paper will present a web-based solution developed to achieve such a goal: the solution leverages the flexibility of the P-BEAST archiver to retrieve data, and exploits the versatility of the Grafana dashboard builder to offer a very rich user experience. Additionally, particular attention will be given to the way some technical challenges (like the efficient visualization of a huge amount of data and the integration of the P-BEAST data source in Grafana) have been faced and solved.
Highlights
The Information Service (IS) [1] is a software infrastructure component of the Trigger and Data Acquisition system (TDAQ) [2] of the ATLAS [3] detector at the Large Hadron Collider (LHC) at CERN
IS is used for the online monitoring of both the TDAQ system and the ATLAS sub-detectors
It is implemented as a set of CORBA [4] server applications running on dedicated computers at the ATLAS experimental area
Summary
The Information Service (IS) [1] is a software infrastructure component of the Trigger and Data Acquisition system (TDAQ) [2] of the ATLAS [3] detector at the Large Hadron Collider (LHC) at CERN. IS does not provide persistent data storage, so if the service is not running any more or information has been updated, the previous IS data are lost and not accessible to experts. 2. User Requirements and Design The high-level functionality provided by this project is a generic mechanism to store, retrieve and visualize ATLAS operational monitoring data. The main users are experts analyzing behavior of different systems of the ATLAS detector, investigating problems, correlating data and comparing differences between data taking sessions. Another group of users are shifters using online dashboards to verify the state of various parameters of the experiment during on-going runs. Data can be accessed via programming interfaces, command line utilities and graphical webbased applications
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