> For the complete documentation index, see [llms.txt](https://docs.groundcover.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.groundcover.com/collect-data/data-sources/prometheus.md).

# Prometheus

Integrate with Prometheus

## Integration Methods

groundcover supports integrating Prometheus metrics through several methods:

1. [**Scraping Metrics in Kubernetes**](/collect-data/data-sources/prometheus/scrape-using-sensor.md)\
   For collecting custom metrics from pods, Prometheus CRDs or additional prometheus endpoints
2. [Scraping Metrics in Standalone Hosts](/collect-data/data-sources/prometheus/scrape-using-sensor-1.md)\
   For collecting custom metrics from services on VMs and standalone machines or additional prometheus endpoints
3. [Scraping Metrics from groundcover backend](/collect-data/data-sources/prometheus/scrape-using-sensor-1.md)\
   For collecting custom metrics from cloud services endpoints
4. [**Direct metric push with Remote Write**](/collect-data/data-sources/prometheus/push-metrics-to-groundcover.md)\
   Directly push metrics into groundcover

## Data Access

After ingestion, access and use your metrics in groundcover:

* Analyze data in the [Explore screen](https://app.groundcover.com/explore/data-explorer)
* Create dashboards in the [Dashboards screen](https://app.groundcover.com/dashboards)
* Set up real-time metric monitors in the [Monitors screen](https://app.groundcover.com/monitors)
* Query metrics via the [Prometheus API endpoint](/reference/remote-access-and-apis/raw-prometheus-and-clickhouse.md)


---

# 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.groundcover.com/collect-data/data-sources/prometheus.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.
