SCADA statistics monitoring using the Elastic Stack (Elasticsearch, Logstash, Kibana)

The Industrial Controls and Safety systems group at CERN, in collaboration with other groups, has developed and currently maintains around 200 controls applications that include domains such as LHC magnet protection, cryogenics and electrical network supervision systems. Millions of value changes and alarms from many devices are archived to a centralised Oracle database but it is not easy to obtain high-level statistics from such an archive. A system based on the Elasticsearch, Logstash and Kibana (the Elastic Stack [1]) has been implemented in order to provide easy access to these statistics. This system provides aggregated statistics based on the number of value changes and alarms, classified according to several criteria such as time, application domain, system and device. The system can be used, for example, to detect abnormal situations and alarm misconfiguration. In addition to these statistics each application generates text-based log files which are parsed, collected and displayed using the Elastic Stack to provide centralised access to all the application logs. Further work will explore the possibilities of combining the statistics and logs to better understand the behaviour of CERN's controls applications