EPJ Web Conf.
Volume 245, 202024th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|Number of page(s)||7|
|Section||1 - Online and Real-time Computing|
|Published online||16 November 2020|
The evolution of the ALICE O2 monitoring system
CERN, Geneva, Switzerland
2 INFN, Bari, Italy
* Corresponding author: firstname.lastname@example.org
Published online: 16 November 2020
The ALICE Experiment was designed to study the physics of strongly interacting matter with heavy-ion collisions at the CERN LHC. A major upgrade of the detector and computing model (O2, Offline-Online) is currently ongoing. The ALICE O2 farm will consist of almost 1000 nodes enabled to read out and process on-the-fly about 27 Tb/s of raw data. To efficiently operate the experiment and the O2 facility a new monitoring system was developed. It will provide a complete overview of the overall health, detect performance degradation and component failures by collecting, processing, storing and visualising data from hardware and software sensors and probes. The core of the system is based on Apache Kafka ensuring high throughput, fault-tolerant and metric aggregation, processing with the help of Kafka Streams. In addition, Telegraf provides operating system sensors, InfluxDB is used as a time-series database, Grafana as a visualisation tool. The above tool selection evolved from the initial version where collectD was used instead of Telegraf, and Apache Flume together with Apache Spark instead of Apache Kafka.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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