Advanced Student Performance Monitoring Microservice

Design a distributed monitoring system for student performance using Kubernetes and Python microservices. Create a complex event-driven architecture that collects real-time student performance data, implements machine learning-based anomaly detection, and provides comprehensive dashboarding. Use Kafka for event streaming, implement gRPC for inter-service communication, and develop a sophisticated alerting system that can detect potential student performance issues before they become critical.