Next Generation Archiver for WinCC OA

Project goal

Our aim is to make control systems used for the LHC more efficient and smarter. We are working to enhance the functionality of WinCC OA (a SCADA tool used widely at CERN) and to apply data-analytics techniques to the recorded monitoring data, in order to detect anomalies and systematic issues that may impact upon system operation and maintenance.

R&D topic
Machine learning and data analytics
Project coordinator(s)
Rafal Kulaga
Team members
Anthony Hennessey, Mariusz Suder, Piotr Golonka, Peter Sollander, Fernando Varela, Marc Bengulescu, Filip Siroky
Collaborator liaison(s)
Thomas Hahn, Juergen Kazmeier, Alexey Fishkin, Tatiana Mangels, Mikhail Kalinkin, Elisabeth Bakany, Ewald Sperrer


Project background

The HL-LHC programme aims to increase the integrated luminosity — and hence the rate of particle collisions — by a factor of ten beyond the LHC’s design value. Monitoring and control systems will therefore become increasingly complex, with unprecedented data throughputs. Consequently, it is vital to further improve the performance of these systems, and to make use of data-analytics algorithms to detect anomalies and anticipate future behaviour. Achieving this involves a number of related lines of work. This project focuses on the development of a modular and future-proof archiving system (NextGen Archiver) that supports different SQL and NOSQL technologies to enable data analytics. It is important that this can be scaled up to meet our requirements beyond 2020.

Recent progress

The most important milestone for the NextGen Archiver (NGA) project in 2020 was the preparation of the first stable version with Oracle and InfluxDB backends for all users at CERN. Despite challenges, it was successfully released in July, receiving positive feedback.

The release is currently being deployed in the ALICE systems, where the NGA will be used with a custom backend to stream data from the control systems to the new physics data readout and analysis architecture after Long Shutdown 2. This represents a crucial validation step for the massive deployment of the new archiver in all CERN systems, planned for Long Shutdown 3.

After the release, the team focused on developing several features and improving reliability. These upgrades will be included in the subsequent versions. One notable upgrade is the ability to send queries to selected backends, with the option to specify different time ranges for each of them. This functionality will be indispensable in systems where parallel archiving into multiple databases is used to improve performance; it will enable new use cases.

Next steps

The work on the project will continue on several fronts. The NGA will be deployed in all systems in the ALICE experiment. A further increase of test coverage is also one of the priorities, with particular attention to performance, handling of failure scenarios, and redundancy. The work on multiple features of the archiver will continue, including extensions to the query mechanisms and improvements in all the backends.


    F. M. Tilaro, R. Kulaga, Siemens Data Analytics and SCADA evolution status report (23 January). Presented at CERN openlab Technical Workshop, Geneva, 2019.
    A. Hennessey, P. Golonka, R. Kulaga, F. V.arela, WinCC Open Architecture – Next Generation Archiver (23 January).