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

# General

> Learn how to monitor your Odin AI instance

## Purpose

The **General** tab gives a real-time system snapshot. It is the first place an admin should check for:

* Platform stability
* Task execution patterns
* AI model activity
* User load

<img src="https://mintcdn.com/odinai/Ep2YKmrk2JutgqAh/img/sa/sa-general.png?fit=max&auto=format&n=Ep2YKmrk2JutgqAh&q=85&s=73162c8fcfed1de62fb4546be54d4d84" alt="General tab overview" width="1293" height="579" data-path="img/sa/sa-general.png" />

***

## Section 1: System Overview

1. **Total Users:** Total number of registered users in your on-prem Odin AI instance. Indicates system adoption across your organization.
2. **Active Projects:** Count of projects that are currently running, being modified, or associated with users/teams. Reflects platform engagement.
3. **System Status:** A quick health indicator. “Healthy” means all components (database, backend workers, LLMs, routing layers) are functioning without errors. If degraded, action is needed.

## Section 2: Task & System Monitoring

This block shows how efficiently the system is processing tasks.

4. **Active Tasks:** Number of tasks currently executing in real time. If 0, the queue is idle. If high, investigate system load or delays.
5. **Task Success Rate:** Percent of tasks that completed successfully. 100% is ideal. A drop may indicate API errors, timeouts, or bad data.
6. **Total Executions (7d):** Total tasks (automations, LLM requests, flows, agents) executed in the last 7 days. Indicates workload trends.
7. **Avg Task Duration:** Time taken per task on average. If duration rises suddenly, it may suggest backend slowness or heavy payloads.
8. **Active Workers:** Number of backend compute agents (workers) currently online and processing. Low worker count can bottleneck execution.

## Section 3: AI & LLM Usage

This section reflects how much AI is being used and how well it’s performing.

9. **LLM Calls (7d):** Total number of requests made to LLMs (Large Language Models) over the past 7 days. Higher count shows greater AI engagement.
10. **LLM Success Rate:** How many LLM requests completed without timeout, failure, or bad output. A success rate below 80% may need tuning or monitoring.
11. **Top AI Tool:** Shows which AI model or tool is most used (e.g., GPT-4, Claude, Odin Custom Agent). “N/A” means no dominant tool used yet.

**Why this matters:** This helps you optimize cost and performance—especially when managing usage across teams or during heavy automation cycles.