The technical support team of a supercomputing centre accumulates, over the course of decades, a large volume of resolved incidents that constitute critical operational knowledge. At the Galician Supercomputing Center (CESGA) this history has been managed for over twenty years with Request Tracker (RT), whose built-in search engine has significant limitations that hinder knowledge reuse by the support staff. This paper presents Fragata, a semantic ticket search system that combines modern information retrieval techniques with the full RT history. The system can find relevant past incidents regardless of language, the presence of typos, or the specific wording of the query. The architecture is deployed on CESGA's infrastructure, supports incremental updates without service interruption, and offloads the most expensive stages to the FinisTerrae III supercomputer. Preliminary results show a substantial qualitative improvement over RT's native search.

翻译：超级计算机中心的技术支持团队历经数十年积累了海量已解决事件，这些构成了关键运营知识。在加利西亚超级计算中心（CESGA），这份历史记录通过请求追踪系统（RT）管理已逾二十年，但其内置搜索引擎存在显著局限，阻碍了支持人员对知识的复用。本文提出FRAGATA——一种结合现代信息检索技术与完整RT历史的语义工单检索系统。该系统能有效检索相关历史事件，不受语言、拼写错误或查询措辞差异的影响。系统架构部署于CESGA基础设施，支持无服务中断的增量更新，并将最耗算力的阶段卸载至FinisTerrae III超级计算机执行。初步结果表明，相较于RT原生搜索，该系统在定性层面实现了显著提升。