Case Study: CERN processes petabytes of data more efficiently with Kubernetes from CNCF

CERN Processing petabytes of data more efficiently with Kubernetes

CERN, the European Organization for Nuclear Research, faced a major scaling challenge as it was storing 330 petabytes of data and anticipated a ten-fold increase from accelerator upgrades. The organization needed a more efficient infrastructure that could handle extreme workload peaks by implementing a hybrid cloud strategy. They turned to the Cloud Native Computing Foundation's open-source technologies, including Kubernetes, to address this.

By implementing the Cloud Native Computing Foundation’s Kubernetes for orchestration along with tools like Helm and Prometheus, CERN achieved remarkable efficiency gains. The solution drastically reduced deployment times, with new cluster creation dropping from over 3 hours to under 15 minutes. The move also reduced virtualization overhead from 20% to ~5%, with expectations of 0% on bare metal and a 10% recovery of memory capacity, allowing more resources to be dedicated to fundamental physics research.

CERN

Ricardo Rocha

Software Engineer