> For the complete documentation index, see [llms.txt](https://docs.eseye.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.eseye.com/api-reference/connectivity-metrics/how-the-data-feed-works-delivery-flow.md).

# How the data feed works (Delivery flow)

## How the data feed works

Connectivity Metrics is delivered as a file-based data feed through SFTP. It is not a REST API and does not require API polling.

Connectivity data is generated continuously as devices authenticate, establish sessions and transfer traffic across Eseye’s network. The data is divided into files at frequent intervals, such as every minute, and made available through an SFTP endpoint.

Your retrieval process collects the files and sends them to your chosen analytics or monitoring platform. The feed can be integrated with data lakes, data warehouses, business intelligence tools, monitoring platforms and security information and event management (SIEM) systems.

### Why Connectivity Metrics uses a file-based feed

A file-based feed provides several benefits when processing connectivity data at scale:

* **Eliminates API polling:** Files can be collected as they become available without making repeated API requests.
* **Supports large data volumes:** File transfers can handle the volume of telemetry generated by large IoT estates without the overhead of processing individual API requests.
* **Integrates with existing data pipelines:** Many organisations already transfer files from SFTP endpoints into their data lakes, warehouses and analytics platforms.

### What you need

You are responsible for retrieving and storing the files. You will need:

* A process that connects to the SFTP endpoint.
* A scheduled job that collects new files.
* An ingestion pipeline that processes the files.
* Sufficient storage for the expected data volume.

Files are generated at frequent intervals, but the collection schedule determines how quickly the data becomes available in your platform. More frequent collection provides a view closer to real time but may require additional processing and storage capacity.

For information about expected data volumes and pricing, see [Data volume and commercial model](/api-reference/connectivity-metrics/data-volume-and-commercial-model.md).

### Related pages

* [Correlate the datasets](/api-reference/connectivity-metrics/correlate-the-datasets.md)
* [Data volume and commercial model](/api-reference/connectivity-metrics/data-volume-and-commercial-model.md)


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