Custom Dashboards

Transform your LLM application data into actionable insights with Langfuse custom dashboards. Create personalized views that track the metrics that matter most to your team - from latency and cost optimization to quality monitoring and user behavior analysis.

Custom dashboards provide a flexible, self-service analytics solution built on a powerful query engine that supports multi-level aggregations across your tracing data. Whether you’re monitoring production performance, analyzing user feedback trends, or correlating costs with quality metrics, dashboards give you the visualization tools to make data-driven decisions.

Key Capabilities

• Flexible Query Engine: Built on the Langfuse data model with support for complex aggregations across traces, observations, users, sessions, and scores
• Rich Visualization Options: Multiple chart types including line charts, bar charts, and time series with customizable layouts
• Advanced Filtering: Filter by metadata, timestamps, user properties, model parameters, and more
• Multi-Level Aggregations: Aggregate data at trace, user, or session levels to answer complex analytical questions
• Real-Time Updates: Dashboards reflect live data from your LLM applications
• Team Collaboration: Share dashboards across your project for unified monitoring and insights
• Langfuse Curated Dashboards: A set of pre-built dashboards focused on Latency, Cost, and Langfuse usage to quickly get started

Quick Start

Get started with custom dashboards in two simple steps or use Langfuse’s curated dashboards right away.

Step 1: Create Your First Widget

Widgets are individual visualization components that display specific metrics from your LLM application data.

1. Navigate to the Dashboards section in your Langfuse project
2. Select the Widgets tab
3. Click New Widget
4. Configure your widget:
   • Data Source: Choose from traces, observations, or user data
   • Metrics: Select what to measure (count, latency, cost, scores, etc.)
   • Dimensions: Group by user, model, time, or custom metadata
   • Filters: Narrow down to specific data subsets
   • Chart Type: Pick the best visualization for your data
5. Click Save to store your widget

Step 2: Build Your Dashboard

Combine multiple widgets into comprehensive dashboards that tell the story of your LLM application performance.

1. Navigate to the Dashboards tab
2. Click New Dashboard
3. Give your dashboard a descriptive name (e.g., “Production Monitoring”, “Cost Analysis”, “Quality Metrics”)
4. Add widgets by selecting from your existing widgets or creating new ones
5. Arrange widgets using the drag-and-drop interface
6. Resize widgets to emphasize important metrics

Leverage Curated Dashboards

Jump-start your analytics with Langfuse-curated dashboards that focus on common LLM application monitoring needs:

• Latency Dashboard: Monitor response times across models and user segments
• Cost Dashboard: Track token usage and associated costs over time
• Usage Dashboard: Understand your Langfuse platform utilization

These pre-built dashboards can be used as-is or cloned and customized to match your specific requirements.

Advanced Features

Advanced Filtering and Grouping

Create precise data views using Langfuse’s powerful filtering capabilities:

• Metadata Filters: Filter by custom metadata attached to traces and observations
• Time-Based Filters: Analyze specific time periods or compare time ranges
• User Properties: Segment by user characteristics and behavior patterns
• Model Parameters: Filter by specific model configurations or versions
• Tags and Labels: Use trace tags for categorical filtering
• Score Thresholds: Filter by quality score ranges or feedback ratings

Chart Types and Visualization

Choose the right visualization for your data:

• Line Charts: Perfect for tracking trends over time (latency, cost, usage)
• Bar Charts: Compare values across categories (models, users, features)
• Time Series: Monitor real-time metrics with temporal granularity
• Pie Charts: Display proportions of categorical data (e.g., feedback ratings)

Dynamic Layout and Responsiveness

• Drag-and-Drop Interface: Easily rearrange widgets to create logical groupings
• Responsive Design: Dashboards adapt to different screen sizes and devices
• Widget Resizing: Emphasize important metrics with larger visualizations
• Grid System: Maintain clean, organized layouts automatically

Use Cases and Examples

Production Monitoring Dashboard

Monitor the health and performance of your LLM application in real-time:

• Error Rate Tracking: Monitor failed requests and error patterns
• Latency Analysis: Track P95 and P99 response times across different endpoints
• Throughput Monitoring: Visualize request volume and capacity utilization
• Model Performance: Compare accuracy and quality metrics across model versions

Cost Optimization Dashboard

Understand and optimize your LLM usage costs:

• Token Usage Trends: Track input/output token consumption over time
• Cost per User: Identify high-usage users and optimize pricing strategies
• Model Cost Comparison: Compare costs across different LLM providers and models
• Feature Cost Analysis: Understand which application features drive the highest costs

Quality and User Experience Dashboard

Monitor the quality and user satisfaction of your LLM application:

• User Feedback Trends: Track thumbs up/down ratings and detailed feedback
• Score Distribution: Visualize the distribution of quality scores over time
• User Behavior Analysis: Understand how users interact with different features
• A/B Test Results: Compare quality metrics between different model versions or prompts

GitHub Discussions