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

# Activity

> See every transaction in real-time

Activity shows individual transactions as they flow through Fenra. Use it to debug issues, investigate anomalies, or monitor live usage.

## What You'll See

A table of transactions with:

| Column          | Description                        |
| --------------- | ---------------------------------- |
| **Timestamp**   | When the transaction was processed |
| **Provider**    | OpenAI, Anthropic, etc.            |
| **Model**       | Specific model used                |
| **Cost**        | Calculated cost in USD             |
| **Feature**     | Your feature name (if provided)    |
| **Environment** | Production, staging, etc.          |

Click any row to see full details.

## Transaction Details

Each transaction includes:

* **Cost Breakdown**: Input cost, output cost, total
* **Usage Metrics**: Token counts, image counts, etc.
* **Context**: All context you sent (feature, environment, user, session)
* **Request ID**: For correlating with your logs

## Filtering

Find specific transactions:

| Filter             | Use Case                                   |
| ------------------ | ------------------------------------------ |
| **Date/Time**      | Last hour, 24 hours, or custom range       |
| **Provider/Model** | Find transactions for specific models      |
| **Cost Range**     | Find expensive transactions (min/max cost) |
| **Environment**    | Production vs. staging                     |
| **Feature**        | Specific product features                  |
| **Request ID**     | Find a specific transaction by ID          |

<Tip>
  Use Cost Range to find outliers. Set a minimum cost (e.g., \$1) to surface expensive transactions.
</Tip>

## Real-Time Mode

Toggle real-time mode to see transactions as they arrive:

* New transactions appear at the top
* Auto-refresh every few seconds
* Perfect for monitoring during deploys or tests

## Common Use Cases

### Debugging

When something looks wrong:

1. Filter to the relevant time window
2. Find the suspicious transactions
3. Check the usage metrics and context
4. Correlate with your application logs using request\_id

### Investigating Cost Spikes

When the dashboard shows a spike:

1. Filter to the spike period
2. Sort by cost (highest first)
3. Look for unusually expensive transactions
4. Check what model, feature, or user caused them

### Monitoring

During launches or experiments:

1. Enable real-time mode
2. Filter to the relevant feature/environment
3. Watch transactions flow in
4. Catch issues immediately

## Export

Download transaction data:

* **CSV**: For spreadsheet analysis
* **JSON**: For programmatic processing

Exports respect your current filters.

## Performance Tips

For large time ranges:

* Use filters to narrow results
* Pagination keeps things responsive
* For deep analysis, export and use external tools

## Related

* [Cost Breakdown](/product-overview/cost-explorer/breakdown): Aggregate analysis
* [Dashboard](/product-overview/dashboard): High-level trends
* [API Reference](/api-reference/introduction): Transaction schema details