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🎯 Overview
This PR introduces comprehensive monitoring infrastructure for the AI Event Concepter application, providing observability across both local Docker development and Kubernetes production environments.
📊 Monitoring Components Implemented
Local Docker Environment Monitoring
Core Monitoring Stack:
Prometheus (port 9090): Central metrics collection and storage with 30-day retention
Grafana (port 3030): Visualization dashboards with pre-configured datasources
Alertmanager (port 9093): Alert routing and notification management
Node Exporter (port 9100): Host system metrics collection
cAdvisor (port 8084): Container resource usage monitoring
PostgreSQL Exporter (port 9187): Database performance metrics
Application Metrics:
Spring Boot Actuator endpoints (/actuator/prometheus) for all microservices
Custom application metrics for business logic monitoring
Health checks and readiness probes for all services
Alerting Rules:
High error rate detection (>10% 5xx responses)
Service availability monitoring (up/down status)
Response time alerts (95th percentile >2s)
Resource usage thresholds (memory >85%, CPU >80%)
Database connection pool monitoring (>90% utilization)
Application startup failure detection
Kubernetes Environment Monitoring
Deployment Strategy:
Helm charts configured for scalable deployment
Service mesh integration ready for advanced monitoring
Ingress configuration with TLS termination
Horizontal Pod Autoscaler (HPA) ready metrics endpoints
Kubernetes-Specific Monitoring:
Pod lifecycle and restart monitoring
Resource requests/limits enforcement
Namespace-level resource tracking
Service discovery integration with Prometheus
ConfigMap and Secret management for monitoring configuration