TailscaleMCP

# Monitoring Stack Architecture This document describes the architecture and design of the Tailscale MCP monitoring stack. ## 🏗️ System Architecture ``` ┌─────────────────────────────────────────────────────────────────┐ │ Tailscale MCP Monitoring Stack │ ├─────────────────────────────────────────────────────────────────┤ │ │ │ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────┐ │ │ │ Grafana │ │ Prometheus │ │ Loki │ │ │ │ (Port 3000) │◄───┤ (Port 9090) │ │ (Port 3100) │ │ │ │ │ │ │ │ │ │ │ │ • Dashboards │ │ • Metrics │ │ • Logs │ │ │ │ • Alerts │ │ • Rules │ │ • Querying │ │ │ │ • Visualization │ │ • Storage │ │ • Analysis │ │ │ └─────────────────┘ └─────────────────┘ └─────────────┘ │ │ ▲ ▲ ▲ │ │ │ │ │ │ │ └───────────────────────┼───────────────────────┘ │ │ │ │ │ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────┐ │ │ │ Promtail │ │ Tailscale MCP │ │ Docker │ │ │ │ │ │ Server │ │ Containers │ │ │ │ • Log Shipping │ │ (Port 8080/9091)│ │ │ │ │ │ • Log Parsing │ │ │ │ • Services │ │ │ │ • Labeling │ │ • Application │ │ • Networks │ │ │ │ │ │ • Metrics │ │ • Volumes │ │ │ │ │ │ • Logs │ │ │ │ │ └─────────────────┘ └─────────────────┘ └─────────────┘ │ │ ▲ ▲ ▲ │ │ │ │ │ │ │ └───────────────────────┼───────────────────────┘ │ │ │ │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ │ Docker Network │ │ │ │ (monitoring) │ │ │ └─────────────────────────────────────────────────────────────┘ │ └─────────────────────────────────────────────────────────────────┘ ``` ## 🔧 Component Details ### Grafana (Visualization Layer) **Purpose**: Provides dashboards, visualization, and alerting for the monitoring stack. **Configuration**: - **Port**: 3000 - **Authentication**: Admin user (admin/admin) - **Data Sources**: Prometheus and Loki - **Dashboards**: 4 comprehensive dashboards - **Plugins**: Pie chart, worldmap panels **Key Features**: - Real-time dashboard updates - Interactive visualizations - Alert rule configuration - Dashboard provisioning - User management ### Prometheus (Metrics Layer) **Purpose**: Collects, stores, and queries time-series metrics from the Tailscale MCP server. **Configuration**: - **Port**: 9090 - **Scrape Interval**: 15 seconds - **Evaluation Interval**: 15 seconds - **Retention**: 200 hours - **Storage**: Local filesystem **Metrics Collection**: - Application metrics from MCP server - System metrics from containers - Custom business metrics - Health check metrics ### Loki (Log Aggregation Layer) **Purpose**: Aggregates, stores, and queries log data from all components. **Configuration**: - **Port**: 3100 - **Storage**: Filesystem-based - **Schema**: v11 - **Retention**: Configurable - **Query Engine**: LogQL **Log Sources**: - Tailscale MCP server logs - Docker container logs - System logs - Application logs ### Promtail (Log Shipping Layer) **Purpose**: Collects logs from various sources and ships them to Loki. **Configuration**: - **Log Sources**: Files, Docker containers, system logs - **Parsing**: JSON, regex, timestamp extraction - **Labeling**: Automatic label assignment - **Shipping**: HTTP push to Loki **Pipeline Stages**: - Log discovery - Log parsing - Label extraction - Log shipping ### Tailscale MCP Server (Application Layer) **Purpose**: The main application that provides Tailscale management functionality. **Configuration**: - **Port**: 8080 (MCP server), 9091 (metrics) - **Logging**: Structured JSON logging - **Metrics**: Prometheus metrics exposure - **Health**: Health check endpoints **Monitoring Integration**: - Prometheus metrics endpoint - Structured logging output - Health check endpoints - Performance metrics ## 📊 Data Flow ### Metrics Flow 1. **Collection**: Tailscale MCP server exposes metrics on port 9091 2. **Scraping**: Prometheus scrapes metrics every 15 seconds 3. **Storage**: Metrics stored in Prometheus time-series database 4. **Querying**: Grafana queries Prometheus for dashboard data 5. **Visualization**: Dashboards display real-time metrics ### Log Flow 1. **Generation**: Tailscale MCP server generates structured JSON logs 2. **Collection**: Promtail collects logs from files and containers 3. **Parsing**: Promtail parses logs and extracts labels 4. **Shipping**: Logs shipped to Loki via HTTP 5. **Storage**: Loki stores logs with indexing 6. **Querying**: Grafana queries Loki with LogQL 7. **Display**: Log streams displayed in dashboards ## 🔄 Service Dependencies ### Startup Order 1. **Loki** - Log storage (no dependencies) 2. **Prometheus** - Metrics storage (no dependencies) 3. **Promtail** - Log shipping (depends on Loki) 4. **Tailscale MCP Server** - Application (depends on Prometheus) 5. **Grafana** - Visualization (depends on Prometheus and Loki) ### Health Checks - **Loki**: HTTP health check on port 3100 - **Prometheus**: HTTP health check on port 9090 - **Promtail**: Process health check - **Tailscale MCP**: HTTP health check on port 9091 - **Grafana**: HTTP health check on port 3000 ## 🛠️ Configuration Management ### Environment Variables ```bash # Tailscale Configuration TAILSCALE_API_KEY=your_api_key_here TAILSCALE_TAILNET=your_tailnet_name_here # Application Configuration LOG_LEVEL=INFO PROMETHEUS_PORT=9091 # Grafana Configuration GF_SECURITY_ADMIN_PASSWORD=admin ``` ### Docker Compose Configuration - **Services**: All components defined as services - **Networks**: Custom Docker network for isolation - **Volumes**: Persistent storage for data - **Environment**: Environment variable injection - **Health Checks**: Service health monitoring ### Configuration Files - **Prometheus**: `monitoring/prometheus/prometheus.yml` - **Loki**: `monitoring/loki/loki.yml` - **Promtail**: `monitoring/promtail/promtail.yml` - **Grafana**: Provisioned via configuration files ## 📈 Scaling Considerations ### Horizontal Scaling - **Multiple Prometheus instances** for high availability - **Loki clustering** for log storage scaling - **Load balancing** for Grafana instances - **Distributed log collection** with multiple Promtail instances ### Vertical Scaling - **Memory allocation** for each component - **CPU allocation** for processing - **Storage allocation** for data retention - **Network bandwidth** for data transfer ## 🔒 Security Architecture ### Network Security - **Docker network isolation** between services - **Internal communication** only - **External access** through specific ports - **Firewall rules** for port access ### Authentication - **Grafana authentication** with admin user - **API key protection** in environment variables - **Service-to-service** authentication - **Access logging** for audit trails ### Data Protection - **Log sanitization** for sensitive data - **Metrics filtering** for privacy - **Encryption** for data at rest - **Backup encryption** for data protection ## 🔄 Monitoring and Alerting ### Health Monitoring - **Service health checks** for all components - **Resource usage monitoring** (CPU, memory, disk) - **Network connectivity monitoring** - **Performance monitoring** for each service ### Alerting Rules - **Service down alerts** for critical services - **Resource usage alerts** for capacity planning - **Error rate alerts** for application issues - **Performance degradation alerts** for optimization ### Notification Channels - **Email notifications** for critical alerts - **Slack integration** for team notifications - **Webhook notifications** for custom integrations - **PagerDuty integration** for on-call management ## 🚀 Deployment Architecture ### Development Environment - **Local Docker Compose** for development - **Hot reloading** for configuration changes - **Debug logging** for troubleshooting - **Test data** for dashboard development ### Production Environment - **Container orchestration** with Docker Swarm or Kubernetes - **High availability** with multiple instances - **Load balancing** for service distribution - **Monitoring** of the monitoring stack itself ### Staging Environment - **Production-like setup** for testing - **Performance testing** with realistic data - **Integration testing** with external services - **User acceptance testing** for dashboards ## 📊 Performance Metrics ### Key Performance Indicators - **Service uptime** for all components - **Response times** for dashboards and queries - **Log processing latency** for real-time monitoring - **Storage utilization** for capacity planning ### Optimization Strategies - **Query optimization** for faster dashboard loading - **Log retention policies** for storage management - **Metrics aggregation** for reduced storage - **Caching strategies** for improved performance --- This architecture provides a robust, scalable, and maintainable monitoring solution for the Tailscale MCP server with comprehensive observability capabilities.