v1.0.0 - Initial Release 🎉
Release v1.0.0 - Initial Release 🎉
Overview
First stable release of the Grafana Observability Stack for AI Agents, providing comprehensive monitoring for AI-agentic systems including GTD Coach, Langfuse, FalkorDB, and MCP servers.
🚀 Features
- Unified AI Operations Dashboard: Single pane of glass for monitoring AI agent health, memory patterns, and performance
- Complete Observability Stack: Grafana, Prometheus, Tempo, and Loki pre-configured with OrbStack networking
- Auto-Discovery: Service inventory that updates automatically
- Visual Pattern Recognition: Identify memory loops, slow responses, and context loss at a glance
📚 Documentation
- Comprehensive technical reference with architecture overview
- AI operations guide with debug scenarios
- Troubleshooting guide with problem-solution patterns
- Quick start instructions and health checks
- Inline operational documentation in all configs
🏗️ Infrastructure
- Docker Compose configuration for easy deployment
- OTLP collection via Grafana Alloy (ports 4317/4318)
- Pre-configured exporters for FalkorDB and Langfuse
- MCP instrumentation wrapper for OpenTelemetry
- Optimized retention policies (90d metrics, 30d traces, 3d logs)
📊 Dashboards Included
- AI Operations Unified Dashboard
- GraphRAG Operations
- APM Traces
- System Resources
🚀 Quick Start
docker compose -f docker-compose.grafana.yml up -d
open http://grafana.local
# Login: admin / admin📋 Requirements
- Docker with Docker Compose
- OrbStack (for automatic *.local domains)
- 4GB RAM minimum, 8GB recommended
🔍 Key Metrics Tracked
- MCP tool invocations and latency
- Memory operation patterns
- Cache hit rates
- GraphRAG memory usage
- Container and host resources
🙏 Acknowledgments
Built with Claude Code assistance for the AI agent monitoring community.
Full Changelog: https://github.com/devops-adeel/grafana-orbstack/commits/v1.0.0