How do you manage and visualize Kubernetes metrics using Prometheus and Grafana?

Prometheus is an open-source monitoring system responsible for collecting and storing metrics data of Kubernetes clusters, such as CPU and memory usage; Grafana is a visualization tool used to create dynamic dashboards. They are crucial for ensuring cluster health, with application scenarios including real-time performance monitoring and fault alerting, enhancing observability and operational efficiency in cloud-native environments.

Core components: Prometheus uses a Pull model to scrape metrics and stores them in a time-series database; Grafana connects to Prometheus through data source plugins to build visual charts. Features include high scalability and real-time querying. In practical applications, monitoring metrics such as Pod status and resource utilization significantly improve cluster reliability and reduce operational costs.

Implementation steps: 1. Deploy Prometheus Operator in Kubernetes; 2. Configure Prometheus data source in Grafana; 3. Design dashboards to visualize metrics. A typical scenario is anomaly detection in production environment monitoring, with business values including resource optimization, rapid fault response, and risk reduction.