| ATLAS Note | |
| Report number | ATL-DAQ-PROC-2017-001 |
| Title | A web-based solution to visualize operational monitoring data in the Trigger and Data Acquisition system of the ATLAS experiment at the LHC |
| Author(s) | Avolio, Giuseppe (European Laboratory for Particle Physics, CERN) ; D'Ascanio, Matteo (European Laboratory for Particle Physics, CERN) ; Lehmann-Miotto, Giovanna (European Laboratory for Particle Physics, CERN) ; Soloviev, Igor (University of California, Irvine) |
| Corporate Author(s) | The ATLAS collaboration |
| Collaboration | ATLAS Collaboration |
| Publication | 2017 |
| Imprint | 15 Jan 2017 |
| Number of pages | 8 |
| In: | J. Phys.: Conf. Ser. 898 (2017) 032010 |
| In: | 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.032010 |
| DOI | 10.1088/1742-6596/898/3/032010 |
| Subject category | Particle Physics - Experiment |
| Accelerator/Facility, Experiment | CERN LHC ; ATLAS |
| Free keywords | ATLAS ; DAQ ; Online ; Operational monitoring ; Time series ; Dashboard ; Grafana |
| 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. |
| Copyright/License | publication: (License: CC-BY-3.0) |
Corresponding record in: Inspire
Record created 2017-01-15, last modified 2019-10-15
PDF