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

# Workspaces Observability

> Monitor, analyze, and optimize AI workspace performance across your organization

The Workspaces Observability module in AI Governance provides deep visibility into the activities, performance, and health of all workspaces across your organization. This powerful monitoring capability enables administrators to track interactions, identify bottlenecks, troubleshoot issues, and optimize performance to ensure AI solutions deliver maximum value.

## Key Features

<CardGroup cols={2}>
  <Card title="Activity Monitoring" icon="chart-mixed">
    Track all interactions and events within workspaces
  </Card>

  <Card title="Performance Analytics" icon="gauge-high">
    Measure execution times and resource efficiency
  </Card>

  <Card title="Automation Tracking" icon="robot">
    Monitor trigger events and automated processes
  </Card>

  <Card title="Error Detection" icon="triangle-exclamation">
    Identify and analyze failures and exceptions
  </Card>

  <Card title="API Monitoring" icon="code">
    Track API calls and integration activities
  </Card>

  <Card title="Visual Flow Analysis" icon="diagram-project">
    Visualize interaction flows and process paths
  </Card>
</CardGroup>

## Who Uses Workspaces Observability?

The Workspaces Observability module serves different roles within the organization.

<Tabs>
  <Tab title="IT Operations">
    IT operations teams use Workspaces Observability to:

    * Monitor overall system health and performance
    * Troubleshoot issues and bottlenecks
    * Track resource utilization and efficiency
    * Identify optimization opportunities
  </Tab>

  <Tab title="AI Engineers">
    AI engineers use Workspaces Observability to:

    * Analyze interaction patterns and performance
    * Debug automated workflows and processes
    * Optimize AI agent behavior and responses
    * Monitor integration points and data flows
  </Tab>

  <Tab title="Security Teams">
    Security teams use Workspaces Observability to:

    * Monitor for unusual activity patterns
    * Investigate potential security incidents
    * Track access and authentication events
    * Validate security control effectiveness
  </Tab>
</Tabs>

## Core Capabilities

### Workspace Overview Monitoring

Get comprehensive visibility into workspace activities and health:

* **Interaction Metrics**: Track total interactions and activity volumes
* **Event Tracking**: Monitor events generated within workspaces
* **API Interaction Analysis**: Measure API calls and integration activity
* **Trigger Monitoring**: Track automation triggers and executions
* **Time Series Analysis**: View activity patterns over time

### Graph Analysis

Visualize and analyze process flows and interaction paths:

* **Visual Flow Mapping**: See how components interact within workspaces
* **Path Analysis**: Identify common and exceptional process paths
* **Bottleneck Detection**: Locate performance constraints in workflows
* **Dependency Mapping**: Visualize relationships between components
* **Time Measurement**: Track execution times along process paths
* **Interactive Exploration**: Drill down into specific paths and nodes

### Automation Monitoring

Track automated processes and their performance:

* **Trigger Analysis**: Monitor events that initiate automated processes
* **Execution Tracking**: Track process completion and success rates
* **Performance Metrics**: Measure execution times and resource usage
* **Error Detection**: Identify failures and exception conditions
* **Trend Analysis**: Monitor automation performance over time
* **Correlation Analysis**: Connect automation activities to outcomes

### Activity Detail Inspection

Examine specific activities and events in detail:

* **Event Details**: View complete information about specific events
* **User Context**: See which users initiated activities
* **Timestamp Analysis**: Track precise timing of activities
* **Parameter Inspection**: Examine inputs and outputs of processes
* **Error Context**: Get detailed information about failures

## Best Practices for Workspace Observability

<CardGroup cols={2}>
  <Card title="Baseline Establishment" icon="chart-line">
    Create performance baselines for comparing future metrics
  </Card>

  <Card title="Proactive Monitoring" icon="bell">
    Set up alerts for unusual patterns or performance issues
  </Card>

  <Card title="Regular Reviews" icon="calendar-check">
    Schedule periodic reviews of observability data
  </Card>

  <Card title="Cross-Metric Analysis" icon="chart-network">
    Correlate multiple metrics to gain deeper insights
  </Card>

  <Card title="Historical Trending" icon="clock-rotate-left">
    Track performance changes over time to identify patterns
  </Card>

  <Card title="Documentation" icon="file-lines">
    Document findings and optimizations for knowledge sharing
  </Card>
</CardGroup>

## Getting Started with Workspaces Observability

<Steps>
  <Step title="Access Workspaces Watcher">
    Navigate to the Workspaces Watcher section in the AI Governance dashboard.
  </Step>

  <Step title="Select a workspace">
    Choose a workspace from the list to start monitoring its activities.

    You can search or filter to find specific workspaces of interest.
  </Step>

  <Step title="Review overview metrics">
    Examine the overview dashboard to get a high-level understanding of workspace activity.
    Pay attention to key metrics like triggers, interactions, and execution times.
  </Step>

  <Step title="Analyze graph data">
    Explore the visual graph to understand process flows and component interactions.\
    Click on nodes and edges to get more detailed information about specific elements.
  </Step>
</Steps>

## Common Observability Scenarios

<Tabs>
  <Tab title="Performance Troubleshooting">
    When addressing performance issues:

    1. Review execution time metrics to identify slow components
    2. Examine the process graph to locate bottlenecks
    3. Check resource utilization during peak activity periods
    4. Analyze error patterns and exception conditions
    5. Compare current performance against historical baselines

    This methodical approach helps pinpoint and resolve performance problems.
  </Tab>

  <Tab title="Usage Pattern Analysis">
    To understand how workspaces are being used:

    1. Analyze interaction volumes across time periods
    2. Identify peak usage times and potential patterns
    3. Examine the most commonly triggered automations
    4. Compare API vs. event-driven interactions
    5. Track user activity patterns and session characteristics

    These insights help optimize workspaces for actual usage patterns.
  </Tab>

  <Tab title="Error Investigation">
    When investigating errors or failures:

    1. Locate error events in the activities log
    2. Examine the context and parameters of failed operations
    3. Analyze the process path leading to the error
    4. Check for correlated errors or warning conditions
    5. Review similar historical incidents for patterns

    This systematic approach helps identify root causes of issues.
  </Tab>

  <Tab title="Capacity Planning">
    For effective capacity planning:

    1. Review workspace utilization trends over time
    2. Identify growth patterns in interactions and API calls
    3. Analyze execution time trends as volume increases
    4. Project future resource needs based on growth patterns
    5. Test scalability through controlled load simulations

    These activities ensure your infrastructure stays ahead of demand.
  </Tab>
</Tabs>

## Key Metrics to Monitor

<CardGroup cols={2}>
  <Card title="Triggers" icon="bolt">
    Number of events that initiate automated processes
  </Card>

  <Card title="Event Interactions" icon="arrow-right-arrow-left">
    Count of interactions driven by events within the system
  </Card>

  <Card title="API Interactions" icon="code-compare">
    Volume of calls to APIs and external services
  </Card>

  <Card title="Execution Time" icon="stopwatch">
    Average and maximum time to complete operations
  </Card>

  <Card title="Error Rate" icon="triangle-exclamation">
    Percentage of operations that result in errors
  </Card>

  <Card title="Resource Utilization" icon="microchip">
    CPU, memory, and network resources consumed
  </Card>
</CardGroup>