Cloud computing and the evolution of management methodologies such as Lean Management or Agile entail a profound transformation in both system construction and maintenance approaches. These practices are encompassed within the term "DevOps." This descriptive approach to an information system or application, alongside the configuration of its constituent components, has necessitated the development of descriptive languages paired with specialized engines for automating systems administration tasks. Among these, the tandem of Ansible (engine) and YAML (descriptive language) stands out as the two most prevalent tools in the market, facing notable competition mainly from Terraform. The current document presents an inquiry into a solution for generating and managing Ansible YAML roles and playbooks, utilizing Generative LLMs (Language Models) to translate human descriptions into code. Our efforts are focused on identifying plausible directions and outlining the potential industrial applications. Note: For the purpose of this experiment, we have opted against the use of Ansible Lightspeed. This is due to its reliance on an IBM Watson model, for which we have not found any publicly available references. Comprehensive information regarding this remarkable technology can be found [1] directly on our partner's website, RedHat.

翻译：云计算以及精益管理、敏捷等管理方法的演进，深刻改变了系统的构建与维护方式。这些实践被统称为"DevOps"。这种对信息系统或应用及其组件配置的描述性方法，催生了配套描述语言与专用引擎的开发，用于自动化系统管理任务。其中，Ansible（引擎）与YAML（描述语言）的组合是市场上最主流的工具，主要面临来自Terraform的显著竞争。本文探讨了一种利用生成式大语言模型（LLM）将人类描述转化为代码，从而生成和管理Ansible YAML角色与剧本的解决方案。我们的工作聚焦于识别可行方向并概述潜在的工业应用。注：本实验中，我们未采用Ansible Lightspeed，因其依赖IBM Watson模型，而该模型尚未发现公开可用的参考文献。关于此项卓越技术的详细信息，可直接参见合作伙伴RedHat的网站[1]。