# Observability - [Overview](https://docs.fiddler.ai/observability/monitoring.md): Monitor production models in real-time with comprehensive observability - [Agentic Observability](https://docs.fiddler.ai/observability/agentic.md): Monitor AI agents and multi-step workflows with specialized dashboards, metrics, and trace visualization - [Custom Metrics](https://docs.fiddler.ai/observability/agentic/custom-metrics.md): Define custom metrics for your agentic and GenAI applications using FQL and span attributes to track business KPIs, quality scores, and operational signals beyond built-in metrics. - [LLM Monitoring](https://docs.fiddler.ai/observability/llm.md): Explore our guide to LLM application monitoring. Learn how Fiddler generates enrichments using trust and safety metrics for alerting, analysis, and debugging. - [LLM-Based Metrics](https://docs.fiddler.ai/observability/llm/llm-based-metrics.md): Explore our guide on LLM-specific metrics useful for evaluating AI-generated content for use cases like chatbots, writing assistants, or content creation tools. - [Embedding Visualizations](https://docs.fiddler.ai/observability/llm/embedding-visualization-with-umap.md): Explore our guide on embedding visualization to enhance LLM monitoring. Discover UMAP techniques, analyze high-dimensional data, and uncover patterns with ease. - [Selecting Enrichments](https://docs.fiddler.ai/observability/llm/selecting-enrichments.md): Learn about Fiddler’s enrichments and monitor key aspects of LLM applications. Discover the different factors to analyze for your specific use case. - [Enrichments](https://docs.fiddler.ai/observability/llm/enrichments.md): Explore our guide on how Fiddler can enrich your LLM application's data to help analyze and evaluate application behavior and performance. - [LLM Evaluation Prompt Specs](https://docs.fiddler.ai/observability/llm/llm-evaluation-prompt-specs.md): Prompt specs is a framework Fiddler provides for leveraging a general-purpose LLM to quickly create custom scoring functions without the need to manually tune an evaluation prompt. - [Monitoring Platform](https://docs.fiddler.ai/observability/platform.md): Dive into our guide to optimizing ML models and LLM applications with Fiddler’s monitoring tools. Learn key metrics to track data drift, performance, and more. - [Alerts](https://docs.fiddler.ai/observability/platform/alerts-platform.md): Discover how to enhance monitoring with Alerts. Learn about alert types and how to set up and view them using the alerts tab in the navigation bar. - [Template-Based Alerts](https://docs.fiddler.ai/observability/platform/template-based-alerts.md): Learn how to create and deploy template-based alerts in Fiddler using Google Sheets and YAML configurations for efficient model monitoring. - [Class Imbalanced Data](https://docs.fiddler.ai/observability/platform/class-imbalanced-data.md): Explore how Fiddler uses weighting to help improve drift detection when class distribution is highly imbalanced. - [Custom Metrics](https://docs.fiddler.ai/observability/platform/custom-metrics.md): Dive into our guide to enhancing ML and LLM insights with custom metrics. Learn to define, add, access, modify, and delete custom metrics in charts and alerts. - [Data Drift](https://docs.fiddler.ai/observability/platform/data-drift-platform.md): Learn about data drift and how Fiddler can monitor your ML model data for drift to provide early detection of issues that could impact model performance. - [Data Integrity](https://docs.fiddler.ai/observability/platform/data-integrity-platform.md): Dive into our guide on ensuring data integrity in ML models and LLMs. Learn to monitor violations with Fiddler’s auto-generated charts and alerts. - [Embedding Visualization](https://docs.fiddler.ai/observability/platform/embedding-visualization-with-umap.md): Dive into our guide on embedding visualization with UMAP in Fiddler. Learn to create charts, select parameters, and interact with visualizations. - [Fiddler Query Language](https://docs.fiddler.ai/observability/platform/fiddler-query-language.md): Explore our guide on using Fiddler Query Language to build custom metrics to drive additional business value in dashboards and extra capability in alerting. - [Model Versions](https://docs.fiddler.ai/observability/platform/model-versions.md): Discover model versions in Fiddler. Learn structured approaches to managing related models, their use cases, capabilities, and how to create a model version. - [Monitoring Charts](https://docs.fiddler.ai/observability/platform/monitoring-charts-platform.md): Explore our guide to the monitoring charts UI. Learn how to create charts, explore functions, customize tabs, and track LLM metrics effectively. - [Performance Tracking](https://docs.fiddler.ai/observability/platform/performance-tracking-platform.md): Learn to track performance with Fiddler. Discover why performance metrics matter and the steps to take when your model isn’t performing as expected. - [Segments](https://docs.fiddler.ai/observability/platform/segments.md): Learn to use model segments for monitoring diverse dimensions. Define, add, and modify segments to gain valuable insights into specific cohorts and dimensions. - [Statistics](https://docs.fiddler.ai/observability/platform/statistics.md): Discover Fiddler’s statistical metrics guide to monitor column aggregations. Learn what’s tracked, how to monitor metrics, and how to set up alerts. - [Traffic](https://docs.fiddler.ai/observability/platform/traffic-platform.md): Learn how Fiddler tracks your ML and GenAI models' traffic patterns and when to take action when traffic patterns deviate from normal. - [Vector Monitoring](https://docs.fiddler.ai/observability/platform/vector-monitoring-platform.md): Dive into our vector monitoring guide to learn about model inputs represented as vectors and how to use Fiddler's custom features to monitor and detect drift. - [Analytics](https://docs.fiddler.ai/observability/analytics.md): Explore our UI guide to Fiddler analytics. Learn about interfaces for various analytics charts and root cause analysis to better understand your models. - [Events Table in RCA](https://docs.fiddler.ai/observability/analytics/data-table-in-rca.md): Learn how to use Fiddler's root cause analysis features to quickly hone in on the data issues adversely impacting your ML models and LLM applications. - [Feature Analytics](https://docs.fiddler.ai/observability/analytics/feature-analytics-chart.md): Dive into our guide on creating feature analytics charts and visualizations for important features in your ML Models and LLM applications. - [Metric Card](https://docs.fiddler.ai/observability/analytics/metric-card.md): Dive into our guide for metric card creation. Follow step-by-step instructions to create metric cards, use custom metrics, right-side controls, and save charts. - [Performance Charts Creation](https://docs.fiddler.ai/observability/analytics/performance-charts-creation.md): Discover our guide to creating performance charts. Learn key steps to select charts, use right-side and in-chart controls, and save your customized charts. - [Performance Charts Visualization](https://docs.fiddler.ai/observability/analytics/performance-charts-visualization.md): Dive into our guide on performance charts and visualizations used to monitor the behavior and performance of your ML models. - [Dashboards](https://docs.fiddler.ai/observability/dashboards.md): Explore our guide to Fiddler’s dashboards for centralized monitoring. Discover key features like filters, utilities, default dashboards, and performance. - [Creating Dashboards](https://docs.fiddler.ai/observability/dashboards/dashboards-creating.md): Navigate our guide for the Dashboard page. Learn how to select new or existing dashboards and access them to monitor performance, drift, integrity, and traffic. - [Dashboard Interactions](https://docs.fiddler.ai/observability/dashboards/dashboard-interactions.md): Explore our guide to dashboard interactions. Learn to remove, edit, zoom into charts, switch between bar and line views, and undo toolbar changes. - [Dashboard Utilities](https://docs.fiddler.ai/observability/dashboards/dashboard-utilities.md): Discover dashboard utilities on Fiddler’s platform. Learn to rename, save, share, copy links, or delete dashboards to manage your collection effortlessly. - [Model UI](https://docs.fiddler.ai/observability/model-ui.md): Learn about Fiddler's no-code Model Editor for streamlined ML model onboarding, featuring draft mode for iterative development and team collaboration. - [Model Editor](https://docs.fiddler.ai/observability/model-ui/model-editor.md): Step-by-step instructions for onboarding ML models using Fiddler's UI-based editor, from dataset upload to schema validation and publication. - [Model Schema Editing](https://docs.fiddler.ai/observability/model-ui/model-schema-editing.md): Learn how to modify numeric ranges, edit categorical features, and add metadata columns to keep your model schema aligned with evolving production data. - [Fairness](https://docs.fiddler.ai/observability/fairness.md): Explore our walkthrough of ML model fairness and bias. 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