> 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/ai-connector/analyze-and-tune-workloads/analyze-across-instances.md).

# Analyze across multiple instances

Run cross-instance analyses over a group of servers selected by tag.

Ask the assistant to analyze a whole group of instances at once, selecting them by tag (TAG): for example every production server, or all instances in a given datacenter.

**Example prompts:**

* "Run a complete I/O analysis across the instances tagged datacenter:dc1 and summarize the hotspots."
* "Find the top resource-consuming production instances over the last 24 hours."

{% @arcade/embed url="<https://app.arcade.software/share/4ZOorXZmb21hH70Nn3ho>" flowId="4ZOorXZmb21hH70Nn3ho" %}

*This walkthrough was recorded with the Claude Desktop app.*

{% hint style="info" %}
**Continue from the menu.** A cross-instance ranking ends with a short menu of next steps: drill into the busiest instance for a full workload analysis, jump straight to the I/O or lock analysis on the worst one, or re-scope to another cohort or a wider window. Pick an option to keep the investigation going without retyping the context.
{% endhint %}


---

# 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/ai-connector/analyze-and-tune-workloads/analyze-across-instances.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.