CERN Accelerating science

ATLAS Slides
Report number	ATL-SOFT-SLIDE-2024-560
Title	Building Scalable Analysis Infrastructure for ATLAS
Author(s)	Gardner Jr, Robert William (University of Chicago (US)) ; Lancon, Eric (Brookhaven National Laboratory (US)) ; Vukotic, Ilija (University of Chicago (US)) ; Bryant, Lincoln (University of Chicago (US)) ; Golnaraghi, Farnaz (University of Chicago (US)) ; Stephen, Judith Lorraine (University of Chicago (US)) ; Taylor, Ryan (University of Victoria (CA)) ; Hu, Fengping (University of Chicago (US))
Corporate author(s)	The ATLAS collaboration
Collaboration	ATLAS Collaboration
Submitted by	lincoln.bryant@cern.ch on 08 Nov 2024
Subject category	Particle Physics - Experiment
Accelerator/Facility, Experiment	CERN LHC ; ATLAS
Free keywords	computing ; analysis facility ; distributed ; kubernetes ; networking
Abstract	We explore the adoption of cloud-native tools and principles to forge flexible and scalable infrastructures, aimed at supporting analysis frameworks being developed for the ATLAS experiment in the High Luminosity Large Hadron Collider (HL-LHC) era. The project culminated in the creation of a federated platform, integrating Kubernetes clusters from various providers such as Tier-2 centers, Tier-3 centers, and from the IRIS-HEP Scalable Systems Laboratory, a National Science Foundation project. A unified interface was provided to streamline the management and scaling of containerized applications. Enhanced system scalability was achieved through integration with analysis facilities, enabling spillover of Jupyter/Binder notebooks and Dask workers to Tier-2 resources. We investigated flexible deployment options for a “stretched” (over the wide area network) cluster pattern, including a centralized “lights out management” model, remote administration of Kubernetes services, and a fully autonomous site-managed cluster approach, to accommodate varied operational and security requirements. The platform demonstrated its efficacy in multi-cluster demonstrators for low-latency analyses and advanced workflows with tools such as Coffea, ServiceX, Uproot and Dask, and RDataFrame, illustrating its ability to support various processing frameworks. The project also resulted in a robust user training infrastructure for ATLAS software and computing on-boarding events.