Abstract
Having information such as an estimation of the processing time or possibility of system outage (abnormal behaviour) helps to assist to monitor system performance and to predict its next state. The current cyber-infrastructure of the ATLAS Production System presents computing conditions in which contention for resources among high-priority data analyses happens routinely, that might lead to significant workload and data handling interruptions. The lack of the possibility to monitor and to predict the behaviour of the analysis process (its duration) and system's state itself provides motivation for a focus on design of the built-in situational awareness analytic tools.
| Original language | English |
|---|---|
| Article number | 032051 |
| Journal | Journal of Physics: Conference Series |
| Volume | 1085 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 18 Oct 2018 |
| Externally published | Yes |
| Event | 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, ACAT 2017 - Seattle, United States Duration: 21 Aug 2017 → 25 Aug 2017 |
ASJC Scopus subject areas
- Physics and Astronomy(all)
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Barreiro Megino, F. H., Borodin, M., Golubkov, D., Grigorieva, M., Gubin, M., Klimentov, A., Korchuganova, T., Maeno, T., Padolski, S., & Titov, M. (2018). Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production System. Journal of Physics: Conference Series, 1085(3), [032051]. https://doi.org/10.1088/1742-6596/1085/3/032051