KubeCon + CloudNativeCon Europe 2025

In particle physics, compute-intensive workloads often involve thousands of "embarrassingly parallel" jobs relying on multi-gigabyte container images. A large fraction of these workloads is executed using software containers. Efficient execution across large-scale computing environments demands advanced caching and image loading techniques to prevent network saturation and reduce startup times. Leveraging the industry-standard containerd runtime, we evaluate snapshotter plugins such as CVMFS (a CERN-developed distributed file system for large-scale software distribution), SOCI, and Stargz, which use "lazy" image loading to optimise performance. This talk includes an analysis of metrics such as container startup time and image data downloaded, alongside usability evaluations in a research environment. We demonstrate how these tools enhance the reusability and reproducibility of physics analyses---insights relevant to broader high-performance computing scenarios.