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

# Discovery

Steadybit automatically discovers your system and makes it available as potential Chaos Engineering targets. Each target is associated with attributes you can use to specify the exact set of targets when designing or running a Chaos Engineering experiment.

What kind of targets are discovered (e.g., containers, hosts, Kubernetes deployments, or JVM applications), and what kind of attributes are associated (e.g., `k8s.cluster-name`, `aws.zone` or `application.name`) depends on the installed extensions.

{% hint style="info" %}
Target discovery is always performed by a Steadybit extension. The discovered metadata is submitted via the Steadybit Agent to the platform.

If you haven't installed any extensions, you aren't seeing any targets and can't make use of Steadybit's Chaos Engineering platform.
{% endhint %}

## Supported Targets

Check out our [Reliability Hub](https://hub.steadybit.com/targets) to learn about which targets are discovered by a Steadybit extension.

## Missing a target? Extend Steadybit!

Are you missing support for a particular technology? No problem, Steadybit is extensible, allowing you to use open- and closed-source extensions to enhance its capabilities. Learn more within our [extension documentation](/integrate-with-steadybit/extensions.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 dynamically by asking a question.

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

```
GET https://docs.steadybit.com/concepts/discovery.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.