Real-time Cognee Monitoring Dashboard with Grafana

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Create a comprehensive Grafana-based monitoring dashboard that connects directly to Cognee's storage systems and provides real-time visibility into all aspects of the knowledge processing pipeline. The dashboard will support all database providers through standardized metrics collection APIs.

Requirements

Core Architecture

1. Metrics Collection Service

• Multi-database metrics collector that works with all supported Cognee database providers
• Database adapter pattern following Cognee's existing infrastructure design
• Configurable collection intervals

2. Grafana Dashboard Components

• Data Processing Pipeline overview with real-time status
• Knowledge Graph Analytics showing growth and structure metrics
• Vector Storage Utilization across different collection types
• System Performance metrics and resource utilization
• Error Monitoring with alerting capabilities

List of Proposed Dashboard Items

1. Overview Dashboard

• System Health Summary: Database connections, active pipelines, error rates
• Data Processing Flow: Files ingested → chunks processed → entities extracted → relationships formed
• Knowledge Graph Growth: Node/edge count over time with growth rate trends
• Resource Utilization: Storage usage across all database types
• Recent Activity: Latest pipeline runs, newly created datasets, recent errors

2. Data Processing Dashboard

• Pipeline Performance: Processing times, throughput, queue depths
• File Processing Status: Success/failure rates by file type, dataset
• Token Usage: Token consumption patterns, LLM API usage
• Processing Bottlenecks: Identification of slow stages in pipeline
• Data Quality Metrics: Validation errors, content extraction success rates

3. Knowledge Graph Analytics Dashboard

• Graph Structure Visualization: Interactive graph topology overview
• Entity Analysis: Most connected entities, entity type distribution
• Relationship Mapping: Relationship frequency, relationship type analysis
• Ontology Coverage: Percentage of entities validated against ontology
• Graph Evolution: How graph structure changes over time

4. System Health Dashboard

• Database Performance: Query latencies, connection pool status
• Memory & Storage: Usage patterns, growth projections
• Error Monitoring: Error types, frequency, impact analysis