> For the complete documentation index, see [llms.txt](https://docs.verge.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.verge.io/plan-and-deploy/es/arquitecturas-de-referencia.md).

# Arquitecturas de referencia

- [Implementaciones de clústeres perimetrales](https://docs.verge.io/plan-and-deploy/es/arquitecturas-de-referencia/edge.md): Arquitectura de referencia para implementar clústeres perimetrales de VergeOS en sucursales y ubicaciones remotas utilizando hardware de bajo consumo y formato pequeño.
- [Implementaciones multitenant](https://docs.verge.io/plan-and-deploy/es/arquitecturas-de-referencia/csp.md): Arquitectura de referencia para proveedores de servicios en la nube que implementan VergeOS como una plataforma IaaS multitenant con aislamiento de inquilinos, asignación de recursos e infraestructura escalable.
- [Implementaciones de clústeres de alto rendimiento](https://docs.verge.io/plan-and-deploy/es/arquitecturas-de-referencia/data-science.md): Arquitectura de referencia para implementar clústeres de alto rendimiento de VergeOS para cargas de trabajo de ciencia de datos, aprendizaje automático y analítica con aceleración GPU y almacenamiento escalable.
- [Arquitectura de referencia de homelab de VergeOS](https://docs.verge.io/plan-and-deploy/es/arquitecturas-de-referencia/homelab.md): Arquitectura de referencia para implementar VergeOS en entornos homelab, que cubre configuraciones de nodo único, clúster de dos nodos y de nivel de producción con almacenamiento multinivel.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.verge.io/plan-and-deploy/es/arquitecturas-de-referencia.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
