> For the complete documentation index, see [llms.txt](https://docs.datasentinel.io/manual/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.datasentinel.io/manual/getting-started/postgresql-clusters/extensions/system_stats.md).

# system\_stats

system\_stats is a PostgreSQL extension that provides functions to access system level statistics that can be used for monitoring

{% hint style="info" %}
This extension is **OPTIONAL** and should be considered solely when you decide to employ the [Agentless approach](/manual/features/other-features/agentless-monitoring.md) for monitoring your PostgreSQL instances**.**
{% endhint %}

### Installation

{% hint style="warning" %}
To be installed in the internal database named **postgres**
{% endhint %}

For detailed installation instructions of the extension, please consult the GitHub repository <https://github.com/EnterpriseDB/system_stats><br>

You need to grant the role monitor\_system\_stats to the monitoring user.

```sql
// example
GRANT monitor_system_stats to datasentinel;
```

### Monitored metrics

When the **system\_stats** extension is installed, Datasentinel (using the [agentless method](/manual/features/other-features/agentless-monitoring.md)) starts gathering system metrics directly from PostgreSQL clusters at regular intervals. This is achieved by running SQL queries, which enables Datasentinel to collect detailed system metrics without needing a local agent on each server.<br>

{% hint style="info" %}
With this setup, you can browse and analyze these metrics with the same level of precision and granularity as you would expect if a local agent were installed.\
\
Refer to [Cluster & System Metrics](/manual/features/key-features/cluster-and-system-metrics.md) for more details.
{% endhint %}

**Metrics**:

* System information
* CPU load
* CPU usage
* Memory usage
* Network usage
* Swap usage
* I/Os statistics
* File-systems usage


---

# 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.datasentinel.io/manual/getting-started/postgresql-clusters/extensions/system_stats.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.