Reproducibility of computational experiments on kubernetes-managed container clouds with hyperflow

Abstract

We propose a comprehensive solution for reproducibility of scientific workflows. We focus particularly on Kubernetes-managed container clouds, increasingly important in scientific computing. Our solution addresses conservation of the scientific procedure, scientific data, execution environment and experiment deployment, while using standard tools in order to avoid maintainability issues that can obstruct reproducibility. We introduce an Experiment Digital Object (EDO), a record published in an open science repository that contains artifacts required to reproduce an experiment. We demonstrate a variety of reproducibility scenarios including experiment repetition (same experiment and conditions), replication (same experiment, different conditions), and propose a smart reuse scenario in which a previous experiment is partially replayed and partially re-executed. The approach is implemented in the HyperFlow workflow management system and experimentally evaluated using a genomic scientific workflow. The experiment is published as an EDO record on the Zenodo platform.