> For the complete documentation index, see [llms.txt](https://docs.datalogz.io/guides/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.datalogz.io/guides/release-notes/archive/2.8.md).

# 2.8

## What’s new

#### Inventory, search & asset health

* **New Inventory landing page** with instant counts for assets, alerts and similarities.
* **Side panel** on every asset with health, owners, and open alerts.
* **Unified search** with richer attributes and filters.
* **CSV export (up to 500 rows)** for quick hand-offs and spreadsheets.

<figure><img src="/files/dKbgHS6z0L891UGNf0t1" alt=""><figcaption></figcaption></figure>

#### Monitoring

* **Monitor list** in Settings for quick enable/disable and housekeeping.

#### Teams

* **Select all projects/workspaces/streams** to run checks at estate scale.

***

### Improvements

**BI Similarity (Phase 1: Power BI)**&#x20;

* Similarity Dashboard to spot clusters of near-duplicate reports/datasets.
* “Accepted” status so teams can acknowledge intentional overlap and reduce noise.

> Tableau support is on the roadmap—ask us about the preview.

**Performance & reliability**

* Leaner back-end processing for faster inventory builds.
* Stability upgrades across Airflow/MWAA jobs (with smarter intermediate file handling).
* Faster alert pages with cleaner navigation and more accurate counts.

**Connectors & metadata**

* Power BI & Tableau: richer inventory attributes and new search views.
* Entra ID (Azure AD): pipeline stability fixes.
* Qlik Sense & NPrinting: improved user/roles extraction reliability.

***

### Bug fixes (highlights)

* Fixed alert page glitches and the Back button on alert details.
* Corrected alerts\_count in Inventory; missing alerts now surface properly.
* Polished radio button styles and various UI inconsistencies.
* Fixed connector edge cases: Connector Details no longer errors during runs.


---

# 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, and the optional `goal` query parameter:

```
GET https://docs.datalogz.io/guides/release-notes/archive/2.8.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.
