Emulating a computing grid in a local environment for feature evaluation

TL;DR

This paper introduces a method to emulate a large-scale computing grid locally, allowing safe and efficient evaluation of new features without disrupting production systems in high-energy physics data analysis.

Contribution

It presents a novel approach for creating a local emulation of a computing grid, facilitating feature testing in a controlled environment.

Findings

Enables safe feature evaluation without affecting production.

Provides a mini clone of the original grid with essential components.

Supports efficient testing of system modifications.

Abstract

The necessity for complex calculations in high-energy physics and large-scale data analysis has led to the development of computing grids, such as the ALICE computing grid at CERN. These grids outperform traditional supercomputers but present challenges in directly evaluating new features, as changes can disrupt production operations and require comprehensive assessments, entailing significant time investments across all components. This paper proposes a solution to this challenge by introducing a novel approach for emulating a computing grid within a local environment. This emulation, resembling a mini clone of the original computing grid, encompasses its essential components and functionalities. Local environments provide controlled settings for emulating grid components, enabling researchers to evaluate system features without impacting production environments. This investigation contributes to the evolving field of computing grids and distributed systems, offering insights into the emulation of a computing grid in a local environment for feature evaluation.