> For the complete documentation index, see [llms.txt](https://apidocs.alphax.cloud/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://apidocs.alphax.cloud/general-architecture.md).

# General Architecture

#### Overview

The architecture of the AlphaX Cloud's Conduit API, as detailed in the provided document, encompasses a comprehensive ecosystem designed to facilitate efficient data flow from field devices to enterprise-level applications. 

<figure><img src="/files/MrSbvUMbfeEDuV1V7rIq" alt=""><figcaption><p>General Architecture of AlphaX API</p></figcaption></figure>

#### The key components of the architecture include:

1. **Field Devices:** These are the initial sources of data, encompassing a variety of sensors and devices deployed in the field.
2. **MQTT Service:** A messaging protocol that allows for the secure and efficient transmission of data between devices and the server.
3. **LoRaWAN Network Server:** This component manages communication between field devices and the network using the LoRaWAN protocol.
4. **AlphaX Web Application:** An interface for users to interact with the system, configure settings, and visualize data.
5. **AlphaX Storage:** The data storage solution within the architecture, designed for high availability and reliability.
6. **Gatekeeper Service:** Manages authentication and authorisation to ensure secure access to system resources.
7. **HTTP GET Services (V4, V6, and V7):** These are the core components allowing for modular data input and output configurations, ensuring flexibility and scalability in data management and integration.
8. **HTTP POST Services:** This is a HTTP Post service designed for trasferring data from other cloud based applications or sensors and devices with HTTP capability

Each component plays a critical role in ensuring that data flows seamlessly from the edge into the enterprise for analysis and consumption, providing a robust framework for managing complex data ecosystems.


---

# 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 dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://apidocs.alphax.cloud/general-architecture.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.