> ## Documentation Index
> Fetch the complete documentation index at: https://arize-ax.mintlify.site/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# February 2025

> New Releases, Enhancements, + Changes

## What's New

February 27, 2025

#### Labeling Queues

Labeling Queues are now live, making dataset annotation more scalable and efficient with features such as:

* **New Annotator Role** – A dedicated RBAC role with focused permissions, ensuring annotators only see assigned records while keeping other data secure.

* **Seamless Queue Creation** – Create Labeling Queues directly from dataset records, with annotations automatically written back for easy tracking.

* **Annotation Resets** – AI Engineers can reset annotations, allowing re-labeling when needed.

* **Flexible Assignment Methods** – Choose between Random or All assignments for annotators in a queue.

* **Fast & Streamlined UI** – Optimized for quick labeling workflows with: Hotkey support, background data fetching & pagination, and background submissions.

[Learn more →](/docs/ax/evaluate/labeling-queues)

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## Enhancements

February 14, 2025

#### Expand/Collapse Rows in the Trace Table

You can now collapse rows to see more data at a glance or expand them to view more text.

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  <img src="https://storage.googleapis.com/arize-phoenix-assets/assets/images/arize-docs-images/traces_collapse.gif" />
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#### Monitor Runtime

Users can now schedule when monitors run. Users can configure their monitors to run:

* Hourly & Daily: Select specific days of the week.

* Daily, Weekly & Monthly: Runs at 12 AM UTC after creation.

* Default Behavior: Monitors will continue running every 3 hours, 7 days a week unless configured otherwise.

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  <img src="https://storage.googleapis.com/arize-phoenix-assets/assets/images/arize-docs-images/5346d34a-image.jpeg" />
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#### Column Specification With Exporting Data

Users can now export only the columns they care about for large datasets, reducing SDK export time by up to 95%.

* Specify which columns of data you'd like to export when exporting data via the [ArizeExportClient](https://arize-client-python.readthedocs.io/en/latest/llm-api/exporter.html)

* When using the `export_model_to_df` function, users can specify the `columns` parameter to only export specific columns.

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#### Create a Dataset from CSV

Users can now upload CSVs as a dataset in Arize. Columns in the file will be attributes that users can access in Experiments or in Prompt Playground. [Learn more →](/docs/ax/develop/datasets/how-to-datasets)

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#### Monitor Improvements

We've made some updates to make monitors more organized, searchable, and user-friendly. Here's what's new:

* Cardless Design – A sleek, modern table view for better readability.

* Project-Level Monitors – LLM and ML monitors now have separate tabs.

* Search & Sort – Find monitors by name or dimension, plus sort by any column.

* Summary Stats – See how many monitors triggered in the last 24 hours

* New LLM Monitor Types – Clearer categories:

  * Custom Metric Monitor → Performance Monitor with a custom metric preselected.

  * Span Property Monitor → Data Quality Monitor for span properties.

  * Evaluation Monitor → Data Quality Monitor for evaluations.

  * Quick Monitor for Errors – Easily enable error count monitoring (count, status\_code = ERROR).

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#### OTEL Tracing Via HTTP

We've added support for HTTP protocol when sending traces to Arize through an OTEL tracer.

* To use:\* S\*pecify `/v1/traces` as the endpoint and `Transport.HTTP` as the transport in our `register` helper

```csharp theme={null}
// tracer_provider = register(
    endpoint="https://otlp.arize.com/v1/traces",     # NEW
    transport=Transport.HTTP,                        # NEW
    space_id=SPACE_ID,
    api_key=API_KEY
    project_name="test-project-http",
)
```

### 📚 New Content

The latest video tutorials, paper readings, ebooks, self-guided learning modules, and technical posts:

🐳 [DeepSeek Deep Dive](https://arize.com/blog/how-deepseek-is-pushing-the-boundaries-of-ai-development/)

🤖 [How to Build an AI Agent](https://arize.com/blog/how-to-build-an-ai-agent/)

🎉 [We Raised \$70M: A Note from our Founders](https://arize.com/blog/arize-ai-raises-70m-series-c-to-build-the-gold-standard-for-ai-evaluation-observability/)

💯 [How 100X AI Uses Phoenix to Supercharge AI-Driven Troubleshooting](https://arize.com/blog/how-100x-ai-uses-phoenix-to-supercharge-ai-driven-troubleshooting/)

🤖 [Understanding Agentic RAG](https://arize.com/blog/understanding-agentic-rag/)

⚙️ [Multiagent Finetuning: A Conversation with Researcher Yilun Du](https://arize.com/blog/multiagent-finetuning-a-conversation-with-researcher-yilun-du/)