# Security Hardening and Compliance Assessment of Kubernetes Control Plane and Workloads
## 4 Security Hardening of Kubernetes Components
### Observability and Auditing
#### 4.5.3 Kubernetes Monitoring  
The standard way to monitor Kubernetes is to use Prometheus and Grafana. Prometheus is a powerful, open-source monitoring tool extensively utilized for Kubernetes observability. It aggregates metrics from multiple components, including kubelet, cAdvisor, and application pods via HTTP endpoints. Prometheus functions through a pull-based model, systematically retrieving metrics from designated targets and archiving them as time-series data. Kubernetes-native service discovery streamlines target management by automatically adjusting to cluster modifications. Prometheus is frequently integrated with Grafana for data visualization, allowing users to develop comprehensive dashboards that emphasize node health, pod utilization, and application performance trends [27; 28]. Figure 15 shows a Prometheus dashboard for Kubernetes:  
Figure 15: Kubernetes dashboard for Prometheus (v3.2.1).  
This integrated stack facilitates anomaly detection, SLA monitoring, and cluster health management. For example, automatic anomaly detection can be integrated with Prometheus data to identify faults before they impact performance, facilitating proactive issue resolution and enhancing operational efficiency [29]. These attributes render Prometheus an essential element of any scalable Kubernetes monitoring strategy.  
Grafana software enhances Prometheus by serving as a visualization and dashboarding tool. Prometheus and Grafana collectively provide an all-encompassing solution for real-time monitoring. This amalgamation is extensively utilized in contemporary cloud-native ecosystems owing to its adaptability, scalability, and open-source characteristics. Figure 16 illustrates an instance of Kubernetes cluster monitoring within Grafana:  
Connecting to Prometheus as a data source allows Grafana to facilitate the development of interactive dashboards for monitoring cluster health, resource utilization, and performance trends. It is intended to monitor containerized microservices and applications operating within extensive Kubernetes ecosystems. Prometheus and Grafana exhibit high scalability, rendering them appropriate for clusters of any magnitude. Prometheus adeptly manages substantial metric volumes and effectively stores time-series data, whereas Grafana proficiently oversees diverse visualizations within intricate Kubernetes ecosystems. This scalability guarantees that organizations can oversee extensive and expanding Kubernetes deployments without compromising performance or reliability.  
In production environments, the data gathered by Fluentd and shown using Prometheus-Grafana dashboards is utilized for active analysis rather than passive observation. Alerts based on thresholds can be established, for instance, CPU or RAM surges, container restarts, or atypical API activity, that initiate automated replies through alerting systems like Alertmanager, Alerta, or Opsgenie. These responses may encompass scaling services, restarting malfunctioning pods, implementing mitigating scripts, or alerting incident response teams. Excessive failed login attempts documented in Fluentd logs can initiate webhook actions that remove access tokens or impose temporary network limitations.