EPJ Web of Conferences (Jan 2024)

Towards a container-based architecture for CMS data acquisition

  • Amoiridis Vassileios,
  • Behrens Ulf,
  • Bocci Andrea,
  • Branson James,
  • Brummer Philipp,
  • Cano Eric,
  • Cittolin Sergio,
  • Da Silva Almeida Da Quintanilha Joao,
  • Darlea Georgiana-Lavinia,
  • Deldicque Christian,
  • Dobson Marc,
  • Dvorak Antonin,
  • Gigi Dominique,
  • Glege Frank,
  • Gomez-Ceballos Guillelmo,
  • Gorniak Patrycja,
  • Gutić Neven,
  • Hegeman Jeroen,
  • Izquierdo Moreno Guillermo,
  • James Thomas Owen,
  • Karimeh Wassef,
  • Kartalas Miltiadis,
  • Krawczyk Rafał Dominik,
  • Li Wei,
  • Long Kenneth,
  • Meijers Frans,
  • Meschi Emilio,
  • Morović Srećko,
  • Orsini Luciano,
  • Paus Christoph,
  • Petrucci Andrea,
  • Pieri Marco,
  • Rabady Dinyar Sebastian,
  • Racz Attila,
  • Rizopoulos Theodoros,
  • Sakulin Hannes,
  • Schwick Christoph,
  • Šimelevičius Dainius,
  • Tzanis Polyneikis,
  • Vazquez Velez Cristina,
  • Žejdl Petr,
  • Zhang Yousen,
  • Zogatova Dominika

DOI
https://doi.org/10.1051/epjconf/202429502031
Journal volume & issue
Vol. 295
p. 02031

Abstract

Read online

The CMS data acquisition (DAQ) is implemented as a service-oriented architecture where DAQ applications, as well as general applications such as monitoring and error reporting, are run as self-contained services. The task of deployment and operation of services is achieved by using several heterogeneous facilities, custom configuration data and scripts in several languages. In this work, we restructure the existing system into a homogeneous, scalable cloud architecture adopting a uniform paradigm, where all applications are orchestrated in a uniform environment with standardized facilities. In this new paradigm DAQ applications are organized as groups of containers and the required software is packaged into container images. Automation of all aspects of coordinating and managing containers is provided by the Kubernetes environment, where a set of physical and virtual machines is unified in a single pool of compute resources. We demonstrate that a container-based cloud architecture provides an acrossthe-board solution that can be applied for DAQ in CMS. We show strengths and advantages of running DAQ applications in a container infrastructure as compared to a traditional application model.