Galaxy-Kubernetes integration: scaling bioinformatics workflows in the cloud
Galaxy-Kubernetes integration: scaling bioinformatics workflows in the cloud
复制标题
Galaxy-Kubernetes 集成：在云中扩展生物信息学工作流程
DOI：
10.1101/488643
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
M. Freeling
中科院分区：
文献类型：
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作者：
J. Bennetzen;J. Swanson;W. Taylor;M. Freeling
制定可重复、可审核和可扩展的数据处理分析工作流程是生物信息学领域的一个重要挑战。最近，软件容器和云计算引入了一种新颖的解决方案来应对这些挑战。它们通过打包工具及其依赖项来简化软件安装、管理和可重复性。在这项工作中，我们为流行的 Galaxy 工作流程环境实现了一个与云提供商无关且可扩展的容器编排设置。该解决方案使 Galaxy 能够通过 Kubernetes 容器编排器在大多数云提供商（例如 Amazon Web Services、Google Cloud 或 OpenStack 等）上运行和卸载作业。可用性 所有代码均已贡献给 Galaxy 项目，并可在 Galaxy 和 Galaxy-kubernetes 存储库中的 https://github.com/galaxyproject/ 上获取（自 Galaxy 17.05 起）。 https://public.phenomenal-h2020.eu/ 是一个示例部署。
Making reproducible, auditable and scalable data-processing analysis workflows is an important challenge in the field of bioinformatics. Recently, software containers and cloud computing introduced a novel solution to address these challenges. They simplify software installation, management and reproducibility by packaging tools and their dependencies. In this work we implemented a cloud provider agnostic and scalable container orchestration setup for the popular Galaxy workflow environment. This solution enables Galaxy to run on and offload jobs to most cloud providers (e.g. Amazon Web Services, Google Cloud or OpenStack, among others) through the Kubernetes container orchestrator. Availability All code has been contributed to the Galaxy Project and is available (since Galaxy 17.05) at https://github.com/galaxyproject/ in the galaxy and galaxy-kubernetes repositories. https://public.phenomenal-h2020.eu/ is an example deployment.