Dashboard Overview

The Noveum.ai dashboard provides comprehensive visibility into your AI application's performance, giving you real-time insights into traces, costs, and system health. Built specifically for AI workloads, it offers both high-level analytics and detailed trace inspection capabilities.

🎯 Key Dashboard Features

Real-Time Traces Monitoring

• Live Trace Stream: Monitor LLM calls, RAG operations, and agent activities in real-time
• Advanced Filtering: Filter by project, environment, status, date ranges, and custom attributes
• Search Functionality: Quickly find specific traces using full-text search across all trace data
• Status Indicators: Visual status badges for success, error, and pending operations

Performance Analytics

• Latency Metrics: Track response times across different operations and time periods
• Cost Analysis: Monitor spending across different LLM providers and operations
• Throughput Monitoring: Observe request volumes and system capacity
• Error Rate Tracking: Identify and monitor failure patterns

Interactive Trace Inspection

• Detailed Trace View: Expand any trace to see complete request/response data
• Span Hierarchy: Navigate complex multi-step operations with visual span trees
• Timing Analysis: Understand where time is spent in your AI operations
• Context Preservation: See how data flows through embeddings, retrievals, and generations

📊 Dashboard Components

Traces List Interface

The main traces interface offers two viewing modes:

Classic Interface

• Tabular view of all traces with sortable columns
• Quick filtering and search capabilities
• Expandable detail panels for trace inspection

Three-Pane Interface

• Directory tree navigation for complex trace hierarchies
• Split-pane view for simultaneous trace browsing and detail inspection
• Advanced filtering with visual feedback

Filter Controls

• Environment Filter: Switch between development, staging, and production
• Project Filter: Focus on specific applications or services
• Status Filter: View only successful, failed, or pending operations
• Date Range: Analyze performance over custom time periods
• Clear Filters: Quick reset to view all traces

Connection Status

• Real-time Status: Monitor connection health to your trace storage
• Error Reporting: Clear error messages when connectivity issues occur
• Refresh Controls: Manual refresh capability for troubleshooting

🔍 Trace Detail Analysis

Comprehensive Trace Information

Each trace provides detailed insights including:

• Basic Metadata: Timestamp, duration, status, project, and environment
• Request Context: User ID, session ID, and custom attributes
• Response Data: Complete LLM responses, tool outputs, and generated content
• Performance Metrics: Token usage, costs, and timing breakdowns
• Error Details: Stack traces and error context when operations fail

Span Analysis

• Operation Types: Automatic categorization of LLM calls, vector searches, tool usage
• Attribute Inspection: View all custom attributes and metadata
• Timing Visualization: Understand operation sequencing and bottlenecks
• Parent-Child Relationships: Navigate complex workflow hierarchies

Flow Visualization

• Interactive Flow Charts: Visual representation of operation sequences
• Dependency Mapping: See how different components interact
• Error Path Analysis: Trace failure points through your system

🎨 Interface Customization

Layout Options

• Responsive Design: Optimized for desktop and mobile viewing
• Panel Sizing: Adjustable interface panels for different screen sizes
• Dark/Light Themes: Switch between themes for comfortable viewing

Data Display

• Sortable Columns: Sort traces by any metric (time, duration, cost, status)
• Configurable Views: Customize which trace attributes are displayed
• Export Capabilities: Download trace data for external analysis

📈 Getting Started with the Dashboard

Initial Setup

1. Connect Your Applications: Ensure your AI applications are instrumented with Noveum SDKs
2. Verify Data Flow: Check the connection status indicator for successful trace ingestion
3. Explore Filters: Use environment and project filters to focus on relevant data

Best Practices

• Set Up Projects: Organize your applications into logical projects for better filtering
• Use Environments: Separate development, staging, and production traces
• Monitor Regularly: Check dashboard daily for performance trends and issues
• Deep Dive on Errors: Use detailed trace inspection to troubleshoot failures

Performance Tips

• Filter Early: Use filters to reduce data volume for faster loading
• Time Range Selection: Limit date ranges for better performance with large datasets
• Regular Refresh: Enable auto-refresh for monitoring live systems

🔗 Integration with Other Platform Features

The dashboard seamlessly integrates with other Noveum platform capabilities:

• Projects: Filter and organize traces by project structure
• Team Collaboration: Share trace URLs with team members for collaborative debugging
• API Access: Export trace data programmatically using the Noveum API
• Alert Systems: Set up notifications based on dashboard metrics

💡 Advanced Features

Custom Attributes

• Search by Attributes: Find traces using custom metadata you've added
• Attribute Filtering: Create complex filters using custom attributes
• Attribute Visualization: See custom data alongside standard metrics

Bulk Operations

• Multi-Select: Select multiple traces for batch operations
• Bulk Export: Download multiple traces simultaneously
• Comparative Analysis: Compare performance across multiple traces

Real-Time Updates

• Live Refresh: Automatic updates as new traces arrive
• Connection Monitoring: Real-time status of your trace ingestion pipeline
• Performance Indicators: Live metrics for system health monitoring

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Ready to dive deeper? Explore Projects & Environments to organize your AI applications, or check out Team Collaboration to share insights with your team.