Building TeamRescue: Finding the Right Expert with FalkorDB

Описание и применение

TeamRescue использует графовую базу FalkorDB для рекомендации эксперта при сбое сервиса, учитывая владельца, зависимости и историю инцидентов. Рекомендация обновляется при изменении доступности, а контекст сохраняется для последующего обзора.

Задача

During an incident, knowing the service owner is useful—but what happens when that person is unavailable?

Результат

TeamRescue successfully recommends an available expert based on graph traversal, and the recommendation adapts when availability changes. Draft handoffs preserve context for future review.

Рабочий процесс

• 1. User queries "Checkout is failing. Who can help?"
• 2. Backend checks for an available owner of the failing service.
• 3. If no owner is available, backend traverses service dependencies to find incidents affecting dependent services.
• 4. Backend selects a person who resolved a related incident and is currently available.
• 5. AI formats the recommendation with supporting evidence (ownership, dependencies, incident history).
• 6. User can save a draft handoff containing the recommendation and context.

Доказательства

When Priya is unavailable and Rahul is available, TeamRescue recommends Rahul based on his previous incident experience.

Источник

The application first checks for an available owner. A person with relevant resolved-incident experience is the fallback.

Источник

TeamRescue lets users save a draft handoff containing the recommended person, service, a note, and supporting context in FalkorDB.

Источник